Suggested Terms for Ambiguous Search Queries

ABSTRACT

In one embodiment, a method includes receiving, from a client system, a character string having n characters entered by the first user into a query field, wherein a term comprising the n th  character of the character string is an ambiguous term, identifying one or more objects corresponding to the ambiguous term based on a calculated probability that the ambiguous term corresponds to the identified objects, sending instructions for presenting a set of suggested queries to the first user, each suggested query from the set of suggested queries corresponding to one of the identified objects and comprising a reference to the corresponding identified object, receiving a selection of a suggested query corresponding to a first object of the identified objects, and sending, responsive to receiving the selection of the suggested query, instructions for modifying the ambiguous term in the query field to include a reference to the first object.

PRIORITY

This application is a continuation under 35 U.S.C. §120 of U.S. patentapplication Ser. No. 14/489,917, filed 18 Sep. 2014, which is acontinuation under 35 U.S.C. §120 of U.S. patent application Ser. No.13/732,101, filed 31 Dec. 2012, issued as U.S. Pat. No. 8,868,603, whichis a continuation-in-part under 35 U.S.C. §120 of U.S. patentapplication Ser. No. 13/556,046, filed 23 Jul. 2012, issued as U.S. Pat.No. 8,751,521, which is a continuation-in-part under 35 U.S.C. §120 ofU.S. patent application Ser. No. 12/763,162, filed 19 Apr. 2010, issuedas U.S. Pat. No. 8,572,129, each of which is incorporated by reference.

TECHNICAL FIELD

This disclosure generally relates to social graphs and performingsearches for objects within a social-networking environment.

BACKGROUND

A social-networking system, which may include a social-networkingwebsite, may enable its users (such as persons or organizations) tointeract with it and with each other through it. The social-networkingsystem may, with input from a user, create and store in thesocial-networking system a user profile associated with the user. Theuser profile may include demographic information, communication-channelinformation, and information on personal interests of the user. Thesocial-networking system may also, with input from a user, create andstore a record of relationships of the user with other users of thesocial-networking system, as well as provide services (e.g. wall posts,photo-sharing, event organization, messaging, games, or advertisements)to facilitate social interaction between or among users.

The social-networking system may transmit over one or more networkscontent or messages related to its services to a mobile or othercomputing device of a user. A user may also install softwareapplications on a mobile or other computing device of the user foraccessing a user profile of the user and other data within thesocial-networking system. The social-networking system may generate apersonalized set of content objects to display to a user, such as anewsfeed of aggregated stories of other users connected to the user.

Social-graph analysis views social relationships in terms of networktheory consisting of nodes and edges. Nodes represent the individualactors within the networks, and edges represent the relationshipsbetween the actors. The resulting graph-based structures are often verycomplex. There can be many types of nodes and many types of edges forconnecting nodes. In its simplest form, a social graph is a map of allof the relevant edges between all the nodes being studied.

SUMMARY OF PARTICULAR EMBODIMENTS

In particular embodiments, in response to a text query received from auser, a social-networking system may generate structured queries thatinclude references to particular social-graph elements. By providingsuggested structured queries in response to a user's text query, thesocial-networking system may provide a powerful way for users of anonline social network to search for elements represented in a socialgraph based on their social-graph attributes and their relation tovarious social-graph elements.

In particular embodiments, the social-networking system may parsequeries containing ambiguous terms with structured queries. Thesocial-networking system may receive an unstructured text query from auser that contains an ambiguous n-gram. In response, thesocial-networking system may access a social graph and then parse thetext query to identify social-graph elements that corresponded toambiguous n-grams from the text query. A term in a query may beambiguous when it possibly matches multiple social-graph elements. Thesocial-networking system may generate a set of structured queries, whereeach structured query corresponds to one of the possible matchingsocial-graph elements. The querying user may then select among thestructured queries to indicate which social-graph element the queryinguser intended to reference with the ambiguous term. In response to thequerying user's selection, the social-networking system may theneffectively lock the ambiguous term to the social-graph element selectedby the querying user, and then generate a new set of structured queriesbased on the selected social-graph element.

In particular embodiments, the social-networking system may generate aset of default structured queries for a page of the online socialnetwork. The social-networking system may identify a page that a user iscurrently viewing or otherwise accessing and then identifying anysocial-graph elements corresponding to that page. The social-graphelements corresponding to a page may be, for example, the nodecorresponding to a user- or concept-profile page, or the nodes/edgesreferenced in a structured query used to generate a particularsearch-results page. The social-networking system may then generate aset of default structured queries for the page based on the identifiedsocial-graph elements for that page. For example, when accessing auser-profile page for the user “Mark”, some of the default structuredqueries for that page may include “Friends of Mark” or “Photos of Mark”.These default structured queries may then be transmitted and presentedto the user.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example network environment associated with asocial-networking system.

FIG. 2 illustrates an example social graph.

FIG. 3 illustrates an example webpage of an online social network.

FIGS. 4A-4H illustrate example queries of the social network.

FIG. 5 illustrates an example method for disambiguating terms in textqueries to generate structured search queries.

FIGS. 6A-6F illustrate example webpages of an online social network.

FIG. 7 illustrates an example method for generating default structuredsearch queries for a page.

FIG. 8 illustrates an example computer system.

DESCRIPTION OF EXAMPLE EMBODIMENTS System Overview

FIG. 1 illustrates an example network environment 100 associated with asocial-networking system. Network environment 100 includes a clientsystem 130, a social-networking system 160, and a third-party system 170connected to each other by a network 110. Although FIG. 1 illustrates aparticular arrangement of client system 130, social-networking system160, third-party system 170, and network 110, this disclosurecontemplates any suitable arrangement of client system 130,social-networking system 160, third-party system 170, and network 110.As an example and not by way of limitation, two or more of client system130, social-networking system 160, and third-party system 170 may beconnected to each other directly, bypassing network 110. As anotherexample, two or more of client system 130, social-networking system 160,and third-party system 170 may be physically or logically co-locatedwith each other in whole or in part. Moreover, although FIG. 1illustrates a particular number of client systems 130, social-networkingsystems 160, third-party systems 170, and networks 110, this disclosurecontemplates any suitable number of client systems 130,social-networking systems 160, third-party systems 170, and networks110. As an example and not by way of limitation, network environment 100may include multiple client system 130, social-networking systems 160,third-party systems 170, and networks 110.

This disclosure contemplates any suitable network 110. As an example andnot by way of limitation, one or more portions of network 110 mayinclude an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local area network (LAN), a wireless LAN (WLAN), a widearea network (WAN), a wireless WAN (WWAN), a metropolitan area network(MAN), a portion of the Internet, a portion of the Public SwitchedTelephone Network (PSTN), a cellular telephone network, or a combinationof two or more of these. Network 110 may include one or more networks110.

Links 150 may connect client system 130, social-networking system 160,and third-party system 170 to communication network 110 or to eachother. This disclosure contemplates any suitable links 150. Inparticular embodiments, one or more links 150 include one or morewireline (such as for example Digital Subscriber Line (DSL) or Data OverCable Service Interface Specification (DOCSIS)), wireless (such as forexample Wi-Fi or Worldwide Interoperability for Microwave Access(WiMAX)), or optical (such as for example Synchronous Optical Network(SONET) or Synchronous Digital Hierarchy (SDH)) links. In particularembodiments, one or more links 150 each include an ad hoc network, anintranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, aportion of the Internet, a portion of the PSTN, a cellulartechnology-based network, a satellite communications technology-basednetwork, another link 150, or a combination of two or more such links150. Links 150 need not necessarily be the same throughout networkenvironment 100. One or more first links 150 may differ in one or morerespects from one or more second links 150.

In particular embodiments, client system 130 may be an electronic deviceincluding hardware, software, or embedded logic components or acombination of two or more such components and capable of carrying outthe appropriate functionalities implemented or supported by clientsystem 130. As an example and not by way of limitation, a client system130 may include a computer system such as a desktop computer, notebookor laptop computer, netbook, a tablet computer, e-book reader, GPSdevice, camera, personal digital assistant (PDA), handheld electronicdevice, cellular telephone, smartphone, other suitable electronicdevice, or any suitable combination thereof. This disclosurecontemplates any suitable client systems 130. A client system 130 mayenable a network user at client system 130 to access network 110. Aclient system 130 may enable its user to communicate with other users atother client systems 130.

In particular embodiments, client system 130 may include a web browser132, such as MICROSOFT INTERNET EXPLORER, GOOGLE CHROME or MOZILLAFIREFOX, and may have one or more add-ons, plug-ins, or otherextensions, such as TOOLBAR or YAHOO TOOLBAR. A user at client system130 may enter a Uniform Resource Locator (URL) or other addressdirecting the web browser 132 to a particular server (such as server162, or a server associated with a third-party system 170), and the webbrowser 132 may generate a Hyper Text Transfer Protocol (HTTP) requestand communicate the HTTP request to server. The server may accept theHTTP request and communicate to client system 130 one or more Hyper TextMarkup Language (HTML) files responsive to the HTTP request. Clientsystem 130 may render a webpage based on the HTML files from the serverfor presentation to the user. This disclosure contemplates any suitablewebpage files. As an example and not by way of limitation, webpages mayrender from HTML files, Extensible Hyper Text Markup Language (XHTML)files, or Extensible Markup Language (XML) files, according toparticular needs. Such pages may also execute scripts such as, forexample and without limitation, those written in JAVASCRIPT, JAVA,MICROSOFT SILVERLIGHT, combinations of markup language and scripts suchas AJAX (Asynchronous JAVASCRIPT and XML), and the like. Herein,reference to a webpage encompasses one or more corresponding webpagefiles (which a browser may use to render the webpage) and vice versa,where appropriate.

In particular embodiments, social-networking system 160 may be anetwork-addressable computing system that can host an online socialnetwork. Social-networking system 160 may generate, store, receive, andtransmit social-networking data, such as, for example, user-profiledata, concept-profile data, social-graph information, or other suitabledata related to the online social network. Social-networking system 160may be accessed by the other components of network environment 100either directly or via network 110. In particular embodiments,social-networking system 160 may include one or more servers 162. Eachserver 162 may be a unitary server or a distributed server spanningmultiple computers or multiple datacenters. Servers 162 may be ofvarious types, such as, for example and without limitation, web server,news server, mail server, message server, advertising server, fileserver, application server, exchange server, database server, proxyserver, another server suitable for performing functions or processesdescribed herein, or any combination thereof. In particular embodiments,each server 162 may include hardware, software, or embedded logiccomponents or a combination of two or more such components for carryingout the appropriate functionalities implemented or supported by server162. In particular embodiments, social-networking system 164 may includeone or more data stores 164. Data stores 164 may be used to storevarious types of information. In particular embodiments, the informationstored in data stores 164 may be organized according to specific datastructures. In particular embodiments, each data store 164 may be arelational database. Particular embodiments may provide interfaces thatenable a client system 130, a social-networking system 160, or athird-party system 170 to manage, retrieve, modify, add, or delete, theinformation stored in data store 164.

In particular embodiments, social-networking system 160 may store one ormore social graphs in one or more data stores 164. In particularembodiments, a social graph may include multiple nodes—which may includemultiple user nodes (each corresponding to a particular user) ormultiple concept nodes (each corresponding to a particular concept)—andmultiple edges connecting the nodes. Social-networking system 160 mayprovide users of the online social network the ability to communicateand interact with other users. In particular embodiments, users may jointhe online social network via social-networking system 160 and then addconnections (i.e., relationships) to a number of other users ofsocial-networking system 160 whom they want to be connected to. Herein,the term “friend” may refer to any other user of social-networkingsystem 160 with whom a user has formed a connection, association, orrelationship via social-networking system 160.

In particular embodiments, social-networking system 160 may provideusers with the ability to take actions on various types of items orobjects, supported by social-networking system 160. As an example andnot by way of limitation, the items and objects may include groups orsocial networks to which users of social-networking system 160 maybelong, events or calendar entries in which a user might be interested,computer-based applications that a user may use, transactions that allowusers to buy or sell items via the service, interactions withadvertisements that a user may perform, or other suitable items orobjects. A user may interact with anything that is capable of beingrepresented in social-networking system 160 or by an external system ofthird-party system 170, which is separate from social-networking system160 and coupled to social-networking system 160 via a network 110.

In particular embodiments, social-networking system 160 may be capableof linking a variety of entities. As an example and not by way oflimitation, social-networking system 160 may enable users to interactwith each other as well as receive content from third-party systems 170or other entities, or to allow users to interact with these entitiesthrough an application programming interfaces (API) or othercommunication channels.

In particular embodiments, a third-party system 170 may include one ormore types of servers, one or more data stores, one or more interfaces,including but not limited to APIs, one or more web services, one or morecontent sources, one or more networks, or any other suitable components,e.g., that servers may communicate with. A third-party system 170 may beoperated by a different entity from an entity operatingsocial-networking system 160. In particular embodiments, however,social-networking system 160 and third-party systems 170 may operate inconjunction with each other to provide social-networking services tousers of social-networking system 160 or third-party systems 170. Inthis sense, social-networking system 160 may provide a platform, orbackbone, which other systems, such as third-party systems 170, may useto provide social-networking services and functionality to users acrossthe Internet.

In particular embodiments, a third-party system 170 may include athird-party content object provider. A third-party content objectprovider may include one or more sources of content objects, which maybe communicated to a client system 130. As an example and not by way oflimitation, content objects may include information regarding things oractivities of interest to the user, such as, for example, movie showtimes, movie reviews, restaurant reviews, restaurant menus, productinformation and reviews, or other suitable information. As anotherexample and not by way of limitation, content objects may includeincentive content objects, such as coupons, discount tickets, giftcertificates, or other suitable incentive objects.

In particular embodiments, social-networking system 160 also includesuser-generated content objects, which may enhance a user's interactionswith social-networking system 160. User-generated content may includeanything a user can add, upload, send, or “post” to social-networkingsystem 160. As an example and not by way of limitation, a usercommunicates posts to social-networking system 160 from a client system130. Posts may include data such as status updates or other textualdata, location information, photos, videos, links, music or othersimilar data or media. Content may also be added to social-networkingsystem 160 by a third-party through a “communication channel,” such as anewsfeed or stream.

In particular embodiments, social-networking system 160 may include avariety of servers, sub-systems, programs, modules, logs, and datastores. In particular embodiments, social-networking system 160 mayinclude one or more of the following: a web server, action logger,API-request server, relevance-and-ranking engine, content-objectclassifier, notification controller, action log,third-party-content-object-exposure log, inference module,authorization/privacy server, search module, ad-targeting module,user-interface module, user-profile store, connection store, third-partycontent store, or location store. Social-networking system 160 may alsoinclude suitable components such as network interfaces, securitymechanisms, load balancers, failover servers,management-and-network-operations consoles, other suitable components,or any suitable combination thereof. In particular embodiments,social-networking system 160 may include one or more user-profile storesfor storing user profiles. A user profile may include, for example,biographic information, demographic information, behavioral information,social information, or other types of descriptive information, such aswork experience, educational history, hobbies or preferences, interests,affinities, or location. Interest information may include interestsrelated to one or more categories. Categories may be general orspecific. As an example and not by way of limitation, if a user “likes”an article about a brand of shoes the category may be the brand, or thegeneral category of “shoes” or “clothing.” A connection store may beused for storing connection information about users. The connectioninformation may indicate users who have similar or common workexperience, group memberships, hobbies, educational history, or are inany way related or share common attributes. The connection informationmay also include user-defined connections between different users andcontent (both internal and external). A web server may be used forlinking social-networking system 160 to one or more client systems 130or one or more third-party system 170 via network 110. The web servermay include a mail server or other messaging functionality for receivingand routing messages between social-networking system 160 and one ormore client systems 130. An API-request server may allow a third-partysystem 170 to access information from social-networking system 160 bycalling one or more APIs. An action logger may be used to receivecommunications from a web server about a user's actions on or offsocial-networking system 160. In conjunction with the action log, athird-party-content-object log may be maintained of user exposures tothird-party-content objects. A notification controller may provideinformation regarding content objects to a client system 130.Information may be pushed to a client system 130 as notifications, orinformation may be pulled from client system 130 responsive to a requestreceived from client system 130. Authorization servers may be used toenforce one or more privacy settings of the users of social-networkingsystem 160. A privacy setting of a user determines how particularinformation associated with a user can be shared. The authorizationserver may allow users to opt in or opt out of having their actionslogged by social-networking system 160 or shared with other systems(e.g., third-party system 170), such as, for example, by settingappropriate privacy settings. Third-party-content-object stores may beused to store content objects received from third parties, such as athird-party system 170. Location stores may be used for storing locationinformation received from client systems 130 associated with users.Ad-pricing modules may combine social information, the current time,location information, or other suitable information to provide relevantadvertisements, in the form of notifications, to a user.

Social Graphs

FIG. 2 illustrates example social graph 200. In particular embodiments,social-networking system 160 may store one or more social graphs 200 inone or more data stores. In particular embodiments, social graph 200 mayinclude multiple nodes—which may include multiple user nodes 202 ormultiple concept nodes 204—and multiple edges 206 connecting the nodes.Example social graph 200 illustrated in FIG. 2 is shown, for didacticpurposes, in a two-dimensional visual map representation. In particularembodiments, a social-networking system 160, client system 130, orthird-party system 170 may access social graph 200 and relatedsocial-graph information for suitable applications. The nodes and edgesof social graph 200 may be stored as data objects, for example, in adata store (such as a social-graph database). Such a data store mayinclude one or more searchable or queryable indexes of nodes or edges ofsocial graph 200.

In particular embodiments, a user node 202 may correspond to a user ofsocial-networking system 160. As an example and not by way oflimitation, a user may be an individual (human user), an entity (e.g.,an enterprise, business, or third-party application), or a group (e.g.,of individuals or entities) that interacts or communicates with or oversocial-networking system 160. In particular embodiments, when a userregisters for an account with social-networking system 160,social-networking system 160 may create a user node 202 corresponding tothe user, and store the user node 202 in one or more data stores. Usersand user nodes 202 described herein may, where appropriate, refer toregistered users and user nodes 202 associated with registered users. Inaddition or as an alternative, users and user nodes 202 described hereinmay, where appropriate, refer to users that have not registered withsocial-networking system 160. In particular embodiments, a user node 202may be associated with information provided by a user or informationgathered by various systems, including social-networking system 160. Asan example and not by way of limitation, a user may provide his or hername, profile picture, contact information, birth date, sex, maritalstatus, family status, employment, education background, preferences,interests, or other demographic information. In particular embodiments,a user node 202 may be associated with one or more data objectscorresponding to information associated with a user. In particularembodiments, a user node 202 may correspond to one or more webpages.

In particular embodiments, a concept node 204 may correspond to aconcept. As an example and not by way of limitation, a concept maycorrespond to a place (such as, for example, a movie theater,restaurant, landmark, or city); a website (such as, for example, awebsite associated with social-network system 160 or a third-partywebsite associated with a web-application server); an entity (such as,for example, a person, business, group, sports team, or celebrity); aresource (such as, for example, an audio file, video file, digitalphoto, text file, structured document, or application) which may belocated within social-networking system 160 or on an external server,such as a web-application server; real or intellectual property (suchas, for example, a sculpture, painting, movie, game, song, idea,photograph, or written work); a game; an activity; an idea or theory;another suitable concept; or two or more such concepts. A concept node204 may be associated with information of a concept provided by a useror information gathered by various systems, including social-networkingsystem 160. As an example and not by way of limitation, information of aconcept may include a name or a title; one or more images (e.g., animage of the cover page of a book); a location (e.g., an address or ageographical location); a website (which may be associated with a URL);contact information (e.g., a phone number or an email address); othersuitable concept information; or any suitable combination of suchinformation. In particular embodiments, a concept node 204 may beassociated with one or more data objects corresponding to informationassociated with concept node 204. In particular embodiments, a conceptnode 204 may correspond to one or more webpages.

In particular embodiments, a node in social graph 200 may represent orbe represented by a webpage (which may be referred to as a “profilepage”). Profile pages may be hosted by or accessible tosocial-networking system 160. Profile pages may also be hosted onthird-party websites associated with a third-party server 170. As anexample and not by way of limitation, a profile page corresponding to aparticular external webpage may be the particular external webpage andthe profile page may correspond to a particular concept node 204.Profile pages may be viewable by all or a selected subset of otherusers. As an example and not by way of limitation, a user node 202 mayhave a corresponding user-profile page in which the corresponding usermay add content, make declarations, or otherwise express himself orherself. As another example and not by way of limitation, a concept node204 may have a corresponding concept-profile page in which one or moreusers may add content, make declarations, or express themselves,particularly in relation to the concept corresponding to concept node204.

In particular embodiments, a concept node 204 may represent athird-party webpage or resource hosted by a third-party system 170. Thethird-party webpage or resource may include, among other elements,content, a selectable or other icon, or other inter-actable object(which may be implemented, for example, in JavaScript, AJAX, or PHPcodes) representing an action or activity. As an example and not by wayof limitation, a third-party webpage may include a selectable icon suchas “like,” “check in,” “eat,” “recommend,” or another suitable action oractivity. A user viewing the third-party webpage may perform an actionby selecting one of the icons (e.g., “eat”), causing a client system 130to transmit to social-networking system 160 a message indicating theuser's action. In response to the message, social-networking system 160may create an edge (e.g., an “eat” edge) between a user node 202corresponding to the user and a concept node 204 corresponding to thethird-party webpage or resource and store edge 206 in one or more datastores.

In particular embodiments, a pair of nodes in social graph 200 may beconnected to each other by one or more edges 206. An edge 206 connectinga pair of nodes may represent a relationship between the pair of nodes.In particular embodiments, an edge 206 may include or represent one ormore data objects or attributes corresponding to the relationshipbetween a pair of nodes. As an example and not by way of limitation, afirst user may indicate that a second user is a “friend” of the firstuser. In response to this indication, social-networking system 160 maytransmit a “friend request” to the second user. If the second userconfirms the “friend request,” social-networking system 160 may createan edge 206 connecting the first user's user node 202 to the seconduser's user node 202 in social graph 200 and store edge 206 associal-graph information in one or more of data stores 24. In theexample of FIG. 2, social graph 200 includes an edge 206 indicating afriend relation between user nodes 202 of user “A” and user “B” and anedge indicating a friend relation between user nodes 202 of user “C” anduser “B.” Although this disclosure describes or illustrates particularedges 206 with particular attributes connecting particular user nodes202, this disclosure contemplates any suitable edges 206 with anysuitable attributes connecting user nodes 202. As an example and not byway of limitation, an edge 206 may represent a friendship, familyrelationship, business or employment relationship, fan relationship,follower relationship, visitor relationship, subscriber relationship,superior/subordinate relationship, reciprocal relationship,non-reciprocal relationship, another suitable type of relationship, ortwo or more such relationships. Moreover, although this disclosuregenerally describes nodes as being connected, this disclosure alsodescribes users or concepts as being connected. Herein, references tousers or concepts being connected may, where appropriate, refer to thenodes corresponding to those users or concepts being connected in socialgraph 200 by one or more edges 206.

In particular embodiments, an edge 206 between a user node 202 and aconcept node 204 may represent a particular action or activity performedby a user associated with user node 202 toward a concept associated witha concept node 204. As an example and not by way of limitation, asillustrated in FIG. 2, a user may “like,” “attended,” “played,”“listened,” “cooked,” “worked at,” or “watched” a concept, each of whichmay correspond to a edge type or subtype. A concept-profile pagecorresponding to a concept node 204 may include, for example, aselectable “check in” icon (such as, for example, a clickable “check in”icon) or a selectable “add to favorites” icon. Similarly, after a userclicks these icons, social-networking system 160 may create a “favorite”edge or a “check in” edge in response to a user's action correspondingto a respective action. As another example and not by way of limitation,a user (user “C”) may listen to a particular song (“Imagine”) using aparticular application (SPOTIFY, which is an online music application).In this case, social-networking system 160 may create a “listened” edge206 and a “used” edge (as illustrated in FIG. 2) between user nodes 202corresponding to the user and concept nodes 204 corresponding to thesong and application to indicate that the user listened to the song andused the application. Moreover, social-networking system 160 may createa “played” edge 206 (as illustrated in FIG. 2) between concept nodes 204corresponding to the song and the application to indicate that theparticular song was played by the particular application. In this case,“played” edge 206 corresponds to an action performed by an externalapplication (SPOTIFY) on an external audio file (the song “Imagine”).Although this disclosure describes particular edges 206 with particularattributes connecting user nodes 202 and concept nodes 204, thisdisclosure contemplates any suitable edges 206 with any suitableattributes connecting user nodes 202 and concept nodes 204. Moreover,although this disclosure describes edges between a user node 202 and aconcept node 204 representing a single relationship, this disclosurecontemplates edges between a user node 202 and a concept node 204representing one or more relationships. As an example and not by way oflimitation, an edge 206 may represent both that a user likes and hasused at a particular concept. Alternatively, another edge 206 mayrepresent each type of relationship (or multiples of a singlerelationship) between a user node 202 and a concept node 204 (asillustrated in FIG. 2 between user node 202 for user “E” and conceptnode 204 for “SPOTIFY”).

In particular embodiments, social-networking system 160 may create anedge 206 between a user node 202 and a concept node 204 in social graph200. As an example and not by way of limitation, a user viewing aconcept-profile page (such as, for example, by using a web browser or aspecial-purpose application hosted by the user's client system 130) mayindicate that he or she likes the concept represented by the conceptnode 204 by clicking or selecting a “Like” icon, which may cause theuser's client system 130 to transmit to social-networking system 160 amessage indicating the user's liking of the concept associated with theconcept-profile page. In response to the message, social-networkingsystem 160 may create an edge 206 between user node 202 associated withthe user and concept node 204, as illustrated by “like” edge 206 betweenthe user and concept node 204. In particular embodiments,social-networking system 160 may store an edge 206 in one or more datastores. In particular embodiments, an edge 206 may be automaticallyformed by social-networking system 160 in response to a particular useraction. As an example and not by way of limitation, if a first useruploads a picture, watches a movie, or listens to a song, an edge 206may be formed between user node 202 corresponding to the first user andconcept nodes 204 corresponding to those concepts. Although thisdisclosure describes forming particular edges 206 in particular manners,this disclosure contemplates forming any suitable edges 206 in anysuitable manner.

Advertising

In particular embodiments, an advertisement may be text (which may beHTML-linked), one or more images (which may be HTML-linked), one or morevideos, audio, one or more ADOBE FLASH files, a suitable combination ofthese, or any other suitable advertisement in any suitable digitalformat presented on one or more webpages, in one or more e-mails, or inconnection with search results requested by a user). In addition or asan alternative, an advertisement may be one or more sponsored stories(e.g. a news-feed or ticker item on social-networking system 160). Asponsored story may be a social action by a user (such as “liking” apage, “liking” or commenting on a post on a page, RSVPing to an eventassociated with a page, voting on a question posted on a page, checkingin to a place, using an application or playing a game, or “liking” orsharing a website) that an advertiser promotes by, for example, havingthe social action presented within a pre-determined area of a profilepage of a user or other page, presented with additional informationassociated with the advertiser, bumped up or otherwise highlightedwithin news feeds or tickers of other users, or otherwise promoted. Theadvertiser may pay to have the social action promoted.

In particular embodiments, an advertisement may be requested for displaywithin social-networking-system webpages, third-party webpages, or otherpages. An advertisement may be displayed in a dedicated portion of apage, such as in a banner area at the top of the page, in a column atthe side of the page, in a GUI of the page, in a pop-up window, in adrop-down menu, in an input field of the page, over the top of contentof the page, or elsewhere with respect to the page. In addition or as analternative, an advertisement may be displayed within an application. Anadvertisement may be displayed within dedicated pages, requiring theuser to interact with or watch the advertisement before the user mayaccess a page or utilize an application. The user may, for example viewthe advertisement through a web browser.

A user may interact with an advertisement in any suitable manner. Theuser may click or otherwise select the advertisement. By selecting theadvertisement, the user may be directed to (or a browser or otherapplication being used by the user) a page associated with theadvertisement. At the page associated with the advertisement, the usermay take additional actions, such as purchasing a product or serviceassociated with the advertisement, receiving information associated withthe advertisement, or subscribing to a newsletter associated with theadvertisement. An advertisement with audio or video may be played byselecting a component of the advertisement (like a “play button”).Alternatively, by selecting the advertisement, the social-networkingsystem 160 may execute or modify a particular action of the user. As anexample and not by way of limitation, advertisements may be includedamong the search results of a search-results page, where sponsoredcontent is promoted over non-sponsored content. As another example andnot by way of limitation, advertisements may be included among suggestedsearch query, where suggested queries that reference the advertiser orits content/products may be promoted over non-sponsored queries.

An advertisement may include social-networking-system functionality thata user may interact with. For example, an advertisement may enable auser to “like” or otherwise endorse the advertisement by selecting anicon or link associated with endorsement. As another example, anadvertisement may enable a user to search (e.g., by executing a query)for content related to the advertiser. Similarly, a user may share theadvertisement with another user (e.g. through social-networking system160) or RSVP (e.g. through social-networking system 160) to an eventassociated with the advertisement. In addition or as an alternative, anadvertisement may include social-networking-system context directed tothe user. For example, an advertisement may display information about afriend of the user within social-networking system 160 who has taken anaction associated with the subject matter of the advertisement.

Typeahead Processes

In particular embodiments, one or more client-side and/or backend(server-side) processes may implement and utilize a “typeahead” featurethat may automatically attempt to match social-graph elements (e.g.,user nodes 202, concept nodes 204, or edges 206) to informationcurrently being entered by a user in an input form rendered inconjunction with a requested webpage (such as, for example, auser-profile page, a concept-profile page, a search-results webpage, oranother suitable page of the online social network), which may be hostedby or accessible in the social-networking system 160. In particularembodiments, as a user is entering text to make a declaration, thetypeahead feature may attempt to match the string of textual charactersbeing entered in the declaration to strings of characters (e.g., names,descriptions) corresponding to user, concepts, or edges and theircorresponding elements in the social graph 200. In particularembodiments, when a match is found, the typeahead feature mayautomatically populate the form with a reference to the social-graphelement (such as, for example, the node name/type, node ID, edgename/type, edge ID, or another suitable reference or identifier) of theexisting social-graph element.

In particular embodiments, as a user types or otherwise enters text intoa form used to add content or make declarations in various sections ofthe user's profile page, home page, or other page, the typeahead processmay work in conjunction with one or more frontend (client-side) and/orbackend (server-side) typeahead processes (hereinafter referred tosimply as “typeahead process”) executing at (or within) thesocial-networking system 160 (e.g., within servers 162), tointeractively and virtually instantaneously (as appearing to the user)attempt to auto-populate the form with a term or terms corresponding tonames of existing social-graph elements, or terms associated withexisting social-graph elements, determined to be the most relevant orbest match to the characters of text entered by the user as the userenters the characters of text. Utilizing the social-graph information ina social-graph database or information extracted and indexed from thesocial-graph database, including information associated with nodes andedges, the typeahead processes, in conjunction with the information fromthe social-graph database, as well as potentially in conjunction withvarious others processes, applications, or databases located within orexecuting within social-networking system 160, may be able to predict auser's intended declaration with a high degree of precision. However,the social-networking system 160 can also provides user's with thefreedom to enter essentially any declaration they wish, enabling usersto express themselves freely.

In particular embodiments, as a user enters text characters into a formbox or other field, the typeahead processes may attempt to identifyexisting social-graph elements (e.g., user nodes 202, concept nodes 204,or edges 206) that match the string of characters entered in the user'sdeclaration as the user is entering the characters. In particularembodiments, as the user enters characters into a form box, thetypeahead process may read the string of entered textual characters. Aseach keystroke is made, the frontend-typeahead process may transmit theentered character string as a request (or call) to the backend-typeaheadprocess executing within social-networking system 160. In particularembodiments, the typeahead processes may communicate via AJAX(Asynchronous JavaScript and XML) or other suitable techniques, andparticularly, asynchronous techniques. In particular embodiments, therequest may be, or comprise, an XMLHTTPRequest (XHR) enabling quick anddynamic sending and fetching of results. In particular embodiments, thetypeahead process may also transmit before, after, or with the request asection identifier (section ID) that identifies the particular sectionof the particular page in which the user is making the declaration. Inparticular embodiments, a user ID parameter may also be sent, but thismay be unnecessary in some embodiments, as the user may already be“known” based on the user having logged into (or otherwise beenauthenticated by) the social-networking system 160.

In particular embodiments, the typeahead process may use one or morematching algorithms to attempt to identify matching social-graphelements. In particular embodiments, when a match or matches are found,the typeahead process may transmit a response (which may utilize AJAX orother suitable techniques) to the user's client system 130 that mayinclude, for example, the names (name strings) or descriptions of thematching social-graph elements as well as, potentially, other metadataassociated with the matching social-graph elements. As an example andnot by way of limitation, if a user entering the characters “pok” into aquery field, the typeahead process may display a drop-down menu thatdisplays names of matching existing profile pages and respective usernodes 202 or concept nodes 204, such as a profile page named or devotedto “poker” or “pokemon”, which the user can then click on or otherwiseselect thereby confirming the desire to declare the matched user orconcept name corresponding to the selected node. As another example andnot by way of limitation, upon clicking “poker,” the typeahead processmay auto-populate, or causes the web browser 132 to auto-populate, thequery field with the declaration “poker”. In particular embodiments, thetypeahead process may simply auto-populate the field with the name orother identifier of the top-ranked match rather than display a drop-downmenu. The user may then confirm the auto-populated declaration simply bykeying “enter” on his or her keyboard or by clicking on theauto-populated declaration.

More information on typeahead processes may be found in U.S. patentapplication Ser. No. 12/763,162, filed 19 Apr. 2010, and U.S. patentapplication Ser. No. 13/556,072, filed 23 Jul. 2012, which areincorporated by reference.

Structured Search Queries

FIG. 3 illustrates an example webpage of an online social network. Inparticular embodiments, a user may submit a query to the social-networksystem 160 by inputting text into query field 350. A user of an onlinesocial network may search for information relating to a specific subjectmatter (e.g., users, concepts, external content or resource) byproviding a short phrase describing the subject matter, often referredto as a “search query,” to a search engine. The query may be anunstructured text query and may comprise one or more text strings (whichmay include one or more n-grams). In general, a user may input anycharacter string into query field 350 to search for content on thesocial-networking system 160 that matches the text query. Thesocial-networking system 160 may then search a data store 164 (or, inparticular, a social-graph database) to identify content matching thequery. The search engine may conduct a search based on the query phraseusing various search algorithms and generate search results thatidentify resources or content (e.g., user-profile pages, content-profilepages, or external resources) that are most likely to be related to thesearch query. To conduct a search, a user may input or transmit a searchquery to the search engine. In response, the search engine may identifyone or more resources that are likely to be related to the search query,each of which may individually be referred to as a “search result,” orcollectively be referred to as the “search results” corresponding to thesearch query. The identified content may include, for example,social-graph elements (i.e., user nodes 202, concept nodes 204, edges206), profile pages, external webpages, or any combination thereof. Thesocial-networking system 160 may then generate a search-results webpagewith search results corresponding to the identified content and transmitthe search-results webpage to the user. The search results may bepresented to the user, often in the form of a list of links on thesearch-results webpage, each link being associated with a differentwebpage that contains some of the identified resources or content. Inparticular embodiments, each link in the search results may be in theform of a Uniform Resource Locator (URL) that specifies where thecorresponding webpage is located and the mechanism for retrieving it.The social-networking system 160 may then transmit the search-resultswebpage to the web browser 132 on the user's client system 130. The usermay then click on the URL links or otherwise select the content from thesearch-results webpage to access the content from the social-networkingsystem 160 or from an external system (such as, for example, athird-party system 170), as appropriate. The resources may be ranked andpresented to the user according to their relative degrees of relevanceto the search query. The search results may also be ranked and presentedto the user according to their relative degree of relevance to the user.In other words, the search results may be personalized for the queryinguser based on, for example, social-graph information, user information,search or browsing history of the user, or other suitable informationrelated to the user. In particular embodiments, ranking of the resourcesmay be determined by a ranking algorithm implemented by the searchengine. As an example and not by way of limitation, resources that aremore relevant to the search query or to the user may be ranked higherthan the resources that are less relevant to the search query or theuser. In particular embodiments, the search engine may limit its searchto resources and content on the online social network. However, inparticular embodiments, the search engine may also search for resourcesor contents on other sources, such as a third-party system 170, theinternet or World Wide Web, or other suitable sources. Although thisdisclosure describes querying the social-networking system 160 in aparticular manner, this disclosure contemplates querying thesocial-networking system 160 in any suitable manner.

In particular embodiments, the typeahead processes described herein maybe applied to search queries entered by a user. As an example and not byway of limitation, as a user enters text characters into a search field,a typeahead process may attempt to identify one or more user nodes 202,concept nodes 204, or edges 206 that match the string of charactersentered search field as the user is entering the characters. As thetypeahead process receives requests or calls including a string orn-gram from the text query, the typeahead process may perform or causesto be performed a search to identify existing social-graph elements(i.e., user nodes 202, concept nodes 204, edges 206) having respectivenames, types, categories, or other identifiers matching the enteredtext. The typeahead process may use one or more matching algorithms toattempt to identify matching nodes or edges. When a match or matches arefound, the typeahead process may transmit a response to the user'sclient system 130 that may include, for example, the names (namestrings) of the matching nodes as well as, potentially, other metadataassociated with the matching nodes. The typeahead process may thendisplay a drop-down menu 300 that displays names of matching existingprofile pages and respective user nodes 202 or concept nodes 204, anddisplays names of matching edges 206 that may connect to the matchinguser nodes 202 or concept nodes 204, which the user can then click on orotherwise select thereby confirming the desire to search for the matcheduser or concept name corresponding to the selected node, or to searchfor users or concepts connected to the matched users or concepts by thematching edges. Alternatively, the typeahead process may simplyauto-populate the form with the name or other identifier of thetop-ranked match rather than display a drop-down menu 300. The user maythen confirm the auto-populated declaration simply by keying “enter” ona keyboard or by clicking on the auto-populated declaration. Upon userconfirmation of the matching nodes and edges, the typeahead process maytransmit a request that informs the social-networking system 160 of theuser's confirmation of a query containing the matching social-graphelements. In response to the request transmitted, the social-networkingsystem 160 may automatically (or alternately based on an instruction inthe request) call or otherwise search a social-graph database for thematching social-graph elements, or for social-graph elements connectedto the matching social-graph elements as appropriate. Although thisdisclosure describes applying the typeahead processes to search queriesin a particular manner, this disclosure contemplates applying thetypeahead processes to search queries in any suitable manner.

In connection with search queries and search results, particularembodiments may utilize one or more systems, components, elements,functions, methods, operations, or steps disclosed in U.S. patentapplication Ser. No. 11/503,093, filed 11 Aug. 2006, U.S. patentapplication Ser. No. 12/977,027, filed 22 Dec. 2010, and U.S. patentapplication Ser. No. 12/978,265, filed 23 Dec. 2010, which areincorporated by reference.

Element Detection and Parsing Ambiguous Terms

FIGS. 4A-4H illustrate example queries of the social network. Inparticular embodiments, in response to a text query received from afirst user (i.e., the querying user), the social-networking system 160may parse the text query and identify portions of the text query thatcorrespond to particular social-graph elements. However, in some cases aquery may include one or more terms that are ambiguous, where anambiguous term is a term that may possibly correspond to multiplesocial-graph elements. To parse the ambiguous term, thesocial-networking system 160 may access a social graph 200 and thenparse the text query to identify the social-graph elements thatcorresponded to ambiguous n-grams from the text query. Thesocial-networking system 160 may then generate a set of structuredqueries, where each structured query corresponds to one of the possiblematching social-graph elements. These structured queries may be based onstrings generated by a grammar model, such that they are rendered in anatural-language syntax with references to the relevant social-graphelements. These structured queries may be presented to the queryinguser, who can then select among the structured queries to indicate whichsocial-graph element the querying user intended to reference with theambiguous term. In response to the querying user's selection, thesocial-networking system 160 may then lock the ambiguous term in thequery to the social-graph element selected by the querying user, andthen generate a new set of structured queries based on the selectedsocial-graph element. FIGS. 4A-4H illustrate various example textqueries in query field 350 and various structured queries generated inresponse in drop-down menus 300 (although other suitable graphical userinterfaces are possible). By providing suggested structured queries inresponse to a user's text query, the social-networking system 160 mayprovide a powerful way for users of the online social network to searchfor elements represented in the social graph 200 based on theirsocial-graph attributes and their relation to various social-graphelements. Structured queries may allow a querying user to search forcontent that is connected to particular users or concepts in the socialgraph 200 by particular edge-types. The structured queries may betransmitted to the first user and displayed in a drop-down menu 300(via, for example, a client-side typeahead process), where the firstuser can then select an appropriate query to search for the desiredcontent. Some of the advantages of using the structured queriesdescribed herein include finding users of the online social networkbased upon limited information, bringing together virtual indexes ofcontent from the online social network based on the relation of thatcontent to various social-graph elements, or finding content related toyou and/or your friends. Although this disclosure describes and FIGS.4A-4H illustrate generating particular structured queries in aparticular manner, this disclosure contemplates generating any suitablestructured queries in any suitable manner.

In particular embodiments, the social-networking system 160 may receivefrom a querying/first user (corresponding to a first user node 202) anunstructured text query. As an example and not by way of limitation, afirst user may want to search for other users who: (1) are first-degreefriends of the first user; and (2) are associated with StanfordUniversity (i.e., the user nodes 202 are connected by an edge 206 to theconcept node 204 corresponding to the school “Stanford”). The first usermay then enter a text query “friends stanford” into query field 350, asillustrated in FIGS. 4A-4B. As the querying user enters this text queryinto query field 350, the social-networking system 160 may providevarious suggested structured queries, as illustrated in drop-down menus300. As used herein, an unstructured text query refers to a simple textstring inputted by a user. The text query may, of course, be structuredwith respect to standard language/grammar rules (e.g. English languagegrammar). However, the text query will ordinarily be unstructured withrespect to social-graph elements. In other words, a simple text querywill not ordinarily include embedded references to particularsocial-graph elements. Thus, as used herein, a structured query refersto a query that contains references to particular social-graph elements,allowing the search engine to search based on the identified elements.Furthermore, the text query may be unstructured with respect to formalquery syntax. In other words, a simple text query will not necessarilybe in the format of a query command that is directly executable by asearch engine (e.g., the text query “friends stanford” could be parsedto form the query command “intersect(school(Stanford University),friends(me)”, which could be executed as a query in a social-graphdatabase). Although this disclosure describes receiving particularqueries in a particular manner, this disclosure contemplates receivingany suitable queries in any suitable manner.

In particular embodiments, social-networking system 160 may parse theunstructured text query (also simply referred to as a search query)received from the first user (i.e., the querying user) to identify oneor more n-grams. In general, an n-gram is a contiguous sequence of nitems from a given sequence of text or speech. The items may becharacters, phonemes, syllables, letters, words, base pairs, prefixes,or other identifiable items from the sequence of text or speech. Then-gram may comprise one or more characters of text (letters, numbers,punctuation, etc.) entered by the querying user. An n-gram of size onecan be referred to as a “unigram,” of size two can be referred to as a“bigram” or “digram,” of size three can be referred to as a “trigram,”and so on. Each n-gram may include one or more parts from the text queryreceived from the querying user. In particular embodiments, each n-grammay comprise a character string (e.g., one or more characters of text)entered by the first user. As an example and not by way of limitation,the social-networking system 160 may parse the text query “friendsstanford” to identify the following n-grams: friends; stanford; friendsstanford. As another example and not by way of limitation, thesocial-networking system 160 may parse the text query “friends in paloalto” to identify the following n-grams: friends; in; palo; alto;friends in; in palo; palo alto; friend in palo; in palo also; friends inpalo alto. In particular embodiments, each n-gram may comprise acontiguous sequence of n items from the text query. Although thisdisclosure describes parsing particular queries in a particular manner,this disclosure contemplates parsing any suitable queries in anysuitable manner.

In particular embodiments, social-networking system 160 may identify aplurality of nodes or a plurality of edges corresponding to one or moreof the n-grams of a text query. Identifying social-graph elements thatcorrespond to an n-gram may be done in a variety of manners, such as,for example, by determining or calculating, for each n-gram identifiedin the text query, a score that the n-gram corresponds to a social-graphelement. The score may be, for example, a confidence score, aprobability, a quality, a ranking, another suitable type of score, orany combination thereof. As an example and not by way of limitation, thesocial-networking system 160 may determine a probability score (alsoreferred to simply as a “probability”) that the n-gram corresponds to asocial-graph element, such as a user node 202, a concept node 204, or anedge 206 of social graph 200. The probability score may indicate thelevel of similarity or relevance between the n-gram and a particularsocial-graph element. There may be many different ways to calculate theprobability. The present disclosure contemplates any suitable method tocalculate a probability score for an n-gram identified in a searchquery. In particular embodiments, the social-networking system 160 maydetermine a probability, p, that an n-gram corresponds to a particularsocial-graph element. The probability, p, may be calculated as theprobability of corresponding to a particular social-graph element, k,given a particular search query, X. In other words, the probability maybe calculated as p=(k|X). As an example and not by way of limitation, aprobability that an n-gram corresponds to a social-graph element maycalculated as an probability score denoted as p_(i,j,k). The input maybe a text query X=(x₁, x₂, . . . , x_(N)), and a set of classes. Foreach (i:j) and a class k, the social-networking system 160 may computep_(i,j,k)=p(class(x_(i:j))=k|X). As an example and not by way oflimitation, the n-gram “stanford” could be scored with respect to thefollowing social-graph elements as follows: school “StanfordUniversity”=0.7; location “Stanford, Calif.”=0.2; user “AllenStanford”=0.1. In this example, because the n-gram “stanford”corresponds to multiple social-graph elements, it may be considered anambiguous n-gram by the social-networking system 160. In other words,the n-gram is not immediately resolvable to a single social-graphelement based on the parsing algorithm used by the social-networkingsystem 160. In particular embodiments, after identifying an ambiguousn-gram, the social-networking system 160 may highlight that n-gram inthe text query to indicate that it may correspond to multiplesocial-graph elements. As an example and not by way of limitation, asillustrated in FIG. 4B the term “Stanford” in query field 350 has beenhighlighted with a dashed-underline to indicate that it may correspondto multiple social-graph elements, as discussed previously. As anotherexample and not by way of limitation, as illustrated in FIGS. 4C and4E-4H the term “facebook” has been highlighted with a dashed-underlineto indicate that it may correspond to multiple social-graph elements.Although this disclosure describes determining whether n-gramscorrespond to social-graph elements in a particular manner, thisdisclosure contemplates determining whether n-grams correspond tosocial-graph elements in any suitable manner. Moreover, although thisdisclosure describes determining whether an n-gram corresponds to asocial-graph element using a particular type of score, this disclosurecontemplates determining whether an n-gram corresponds to a social-graphelement using any suitable type of score.

In particular embodiments, the social-networking system 160 maydetermine the probability that a particular n-gram corresponds to asocial-graph element based social-graph information. As an example andnot by way of limitation, when determining a probability, p, that ann-gram corresponds to a particular social-graph element, the calculationof the probability may also factor in social-graph information. Thus,the probability of corresponding to a particular social-graph element,k, given a particular search query, X, and social-graph information, G,may be calculated as p=(k|X,G). In particular embodiments, theprobability that an n-gram corresponds to a particular node may be basedon the degree of separation between the first user node 202 and theparticular node. A particular n-gram may have a higher probability ofcorresponding to a social-graph element that is closer in the socialgraph 200 to the querying user (i.e., fewer degrees of separationbetween the element and the first user node 202) than a social-graphelement that is further from the user (i.e., more degrees ofseparation). As an example and not by way of limitation, referencingFIG. 3, if user “B” inputs a text query of “chicken,” the calculatedprobability that this corresponds to the concept node 204 for the recipe“Chicken Parmesan,” which is connected to user “B” by an edge 206, maybe higher than the calculated probability that this n-gram correspondsto other nodes associated with the n-gram chicken (e.g., concept nodes204 corresponding to “chicken nuggets,” or “funky chicken dance”) thatare not connected to user “B” in the social graph 200. In particularembodiments, the probability that an n-gram corresponds to a particularnode may be based on the search history associated with the queryinguser. Social-graph elements that the querying user has previouslyaccessed, or are relevant to the social-graph elements that the queryinguser has previously accessed, may be more likely to be the target of thequerying user's search query. As an example and not by way oflimitation, if first user has previously visited a the “FacebookCulinary Team” profile page, but has never visited the “Facebook Studio”profile page, when determining the probability that the n-gram“facebook” corresponds to either of the concept nodes 204 correspondingto these pages, the social-networking system 160 may determine that theconcept node 204 for “Facebook Culinary Team” has a relatively higherprobability of corresponding to the n-gram “facebook” because thequerying user has previously accessed that concept node 204 (and may infact already be connected to that node with a “viewed” edge 206).Although this disclosure describes determining whether n-gramscorrespond to social-graph elements in a particular manner, thisdisclosure contemplates determining whether n-grams correspond tosocial-graph elements in any suitable manner.

In particular embodiments, social-networking system 160 may identify oneor more edges 206 having a probability greater than an edge-thresholdprobability. Each of the identified edges 206 may correspond to at leastone of the n-grams. As an example and not by way of limitation, then-gram may only be identified as corresponding to an edge, k, ifp_(i,j,k)>p_(edge-threshold). In particular embodiments, thesocial-networking system 160 may identify a plurality of edges 206 (oredge types) as corresponding to a particular n-gram. In such a case, then-gram may be considered an ambiguous n-gram by the social-networkingsystem 160 because multiple edges have a probability, p_(i,j,k), that isgreater than p_(edge-threshold). As an example and not by way oflimitation, the n-gram “work” could be scored with respect to thefollowing social-graph elements as follows: edge-type “work at”=0.6;edge-type “worked at”=0.39; edge-type “lives in”=0.01. If theedge-threshold probability is equal to 0.25, then the edge-typescorresponding to “work at” and “worked at” may be identified becausethey have probabilities greater than the edge-threshold probability,while the edge-type corresponding to “lives in” would not be identifiedbecause its probability is not greater than the edge-thresholdprobability. Consequently, because the social-networking system 160identified multiple edge-types as corresponding to the n-gram “work”,that n-gram may be considered ambiguous. In particular embodiments, eachof the identified edges 206 may be connected to at least one of theidentified nodes. In other words, the social-networking system 160 mayonly identify edges 206 or edge-types that are connected to user nodes202 or concept nodes 204 that have previously been identified ascorresponding to a particular n-gram. Although this disclosure describesidentifying edges 206 that correspond to n-grams in a particular manner,this disclosure contemplates identifying edges 206 that correspond ton-grams in any suitable manner.

In particular embodiments, social-networking system 160 may identify oneor more user nodes 202 or concept nodes 204 having a probability greaterthan a node-threshold probability. Each of the identified nodes maycorrespond to at least one of the n-grams. As an example and not by wayof limitation, the n-gram may only be identified as corresponding to anode, k, if p_(i,j,k)>p_(node-threshold). In particular embodiments, thesocial-networking system 160 may identify a plurality of edges 206 (oredge types) as corresponding to a particular n-gram. In such a case, then-gram may be considered an ambiguous n-gram by the social-networkingsystem 160 because multiple edges have a probability, p_(i,j,k), that isgreater than p_(edge-threshold). As an example and not by way oflimitation, the n-gram “facebook” could be scored with respect to thefollowing social-graph elements as follows: company “Facebook”=0.8;group “Facebook Culinary Team”=0.15; website “Facebook Studio”=0.05. Ifthe node-threshold probability is equal to 0.1, then the concept nodes204 corresponding to “Facebook” and “Facebook Culinary Team” may beidentified because they have probabilities greater than thenode-threshold probability, while the concept node 204 corresponding to“Facebook Studio” would not be identified because its probability is notgreater than the node-threshold probability. Consequently, because thesocial-networking system 160 identified multiple concept nodes 204 ascorresponding to the n-gram “facebook”, that n-gram may be consideredambiguous. In particular embodiments, each of the identified user nodes202 or concept nodes 204 may be connected to at least one of theidentified edges 206. In other words, the social-networking system 160may only identify nodes or nodes-types that are connected to edges 206that have previously been identified as corresponding to a particularn-gram. In particular embodiments, the social-networking system 160 mayonly identify nodes that are within a threshold degree of separation ofthe user node 202 corresponding to the first user (i.e., the queryinguser). The threshold degree of separation may be, for example, one, two,three, or all. Although this disclosure describes identifying nodes thatcorrespond to n-grams in a particular manner, this disclosurecontemplates identifying nodes that correspond to n-grams in anysuitable manner.

Generating Structured Search Queries

In particular embodiments, the social-networking system 160 may access acontext-free grammar model comprising a plurality of grammars. Eachgrammar of the grammar model may comprise one or more non-terminaltokens (or “non-terminal symbols”) and one or more terminal tokens (or“terminal symbols”/“query tokens”), where particular non-terminal tokensmay be replaced by terminal tokens. A grammar model is a set offormation rules for strings in a formal language. Although thisdisclosure describes accessing particular grammars, this disclosurecontemplates any suitable grammars.

In particular embodiments, the social-networking system 160 may generateone or more strings using one or more grammars. To generate a string inthe language, one begins with a string consisting of only a single startsymbol. The production rules are then applied in any order, until astring that contains neither the start symbol nor designatednon-terminal symbols is produced. In a context-free grammar, theproduction of each non-terminal symbol of the grammar is independent ofwhat is produced by other non-terminal symbols of the grammar. Thenon-terminal symbols may be replaced with terminal symbols (i.e.,terminal tokens or query tokens). Some of the query tokens maycorrespond to identified nodes or identified edges, as describedpreviously. A string generated by the grammar may then be used as thebasis for a structured query containing references to the identifiednodes or identified edges. The string generated by the grammar may berendered in a natural-language syntax, such that a structured querybased on the string is also rendered in natural language. A context-freegrammar is a grammar in which the left-hand side of each production ruleconsists of only a single non-terminal symbol. A probabilisticcontext-free grammar is a tuple <Σ, N, S, P>, where the disjoint sets Σand N specify the terminal and non-terminal symbols, respectively, withSεN being the start symbol. P is the set of productions, which take theform E→ξ(p), with EεN, ξε(Σ∪N)⁺, and p=Pr(E→ξ), the probability that Ewill be expanded into the string ξ. The sum of probabilities p over allexpansions of a given non-terminal E must be one. Although thisdisclosure describes generating strings in a particular manner, thisdisclosure contemplates generating strings in any suitable manner.

In particular embodiments, the social-networking system 160 may generateone or more structured queries. The structured queries may be based onthe natural-language strings generated by one or more grammars, asdescribed previously. Each structured query may include references toone or more of the identified nodes or one or more of the identifiededges 206. This type of structured query may allow the social-networkingsystem 160 to more efficiently search for resources and content relatedto the online social network (such as, for example, profile pages) bysearching for content connected to or otherwise related to theidentified user nodes 202 and the identified edges 206. As an exampleand not by way of limitation, in response to the text query, “show mefriends of my girlfriend,” the social-networking system 160 may generatea structured query “Friends of Stephanie,” where “Friends” and“Stephanie” in the structured query are references corresponding toparticular social-graph elements. The reference to “Stephanie” wouldcorrespond to a particular user node 202 (where the social-networkingsystem 160 has parsed the n-gram “my girlfriend” to correspond with auser node 202 for the user “Stephanie”), while the reference to“Friends” would correspond to friend-type edges 206 connecting that usernode 202 to other user nodes 202 (i.e., edges 206 connecting to“Stephanie's” first-degree friends). When executing this structuredquery, the social-networking system 160 may identify one or more usernodes 202 connected by friend-type edges 206 to the user node 202corresponding to “Stephanie”. As another example and not by way oflimitation, as illustrated in FIG. 4E, in response to the text query,“friends who like facebook,” the social-networking system 160 maygenerate a structured query “Friends who like Facebook,” where“Friends,” “like,” and “Facebook” in the structured query are referencescorresponding to particular social-graph elements as describedpreviously (i.e., a friend-type edge 206, a like-type edge 206, andconcept node 204 corresponding to the company “Facebook”). Although thisdisclosure describes generating particular structured queries in aparticular manner, this disclosure contemplates generating any suitablestructured queries in any suitable manner.

In particular embodiments, social-networking system 160 may rank thegenerated structured queries. The structured queries may be ranked basedon a variety of factors. Where the text query received from the queryinguser contains an ambiguous n-gram, the suggested structured queriesgenerated in response to that text query may be ranked, for example, inorder of the probability or likelihood that the identified nodes/edgesreferenced in those structured queries match the intent of the queryinguser, as determined by the social-networking system 160. After rankingthe structured queries, the social-networking system 160 may thentransmit only those structured queries having a rank greater than athreshold rank (e.g., the top seven ranked queries may be transmitted tothe querying user and displayed in a drop-down menu 300). In particularembodiments, the rank for a structured query may be based on the degreeof separation between the user node 202 of the querying user and theparticular social-graph elements referenced in the structured query.Structured queries that reference social-graph elements that are closerin the social graph 200 to the querying user (i.e., fewer degrees ofseparation between the element and the querying user's user node 202)may be ranked more highly than structured queries that referencesocial-graph elements that are further from the user (i.e., more degreesof separation). In particular embodiments, the social-networking system160 may rank the structured queries based on a search history associatedwith the querying user. Structured queries that reference social-graphelements that the querying user has previously accessed, or are relevantto the social-graph elements the querying user has previously accessed,may be more likely to be the target of the querying user's search query.Thus, these structured queries may be ranked more highly. As an exampleand not by way of limitation, if querying user has previously visitedthe “Stanford University” profile page but has never visited the“Stanford, Calif.” profile page, when determining the rank forstructured queries referencing these concepts, the social-networkingsystem 160 may determine that the structured query referencing theconcept node 204 for “Stanford University” has a relatively high rankbecause the querying user has previously accessed the concept node 204for the school. In particular embodiments, the social-networking system160 may rank the structured queries based on advertising sponsorship. Anadvertiser (such as, for example, the user or administrator of aparticular profile page corresponding to a particular node) may sponsora particular node such that a structured query referencing that node maybe ranked more highly. Although this disclosure describes rankingstructured queries in a particular manner, this disclosure contemplatesranking structured queries in any suitable manner.

More information on generating structured queries and grammar models maybe found in U.S. patent application Ser. No. 13/674,695, filed 12 Nov.2012, and U.S. patent application Ser. No. 13/731,866, filed 31 Dec.2012, each of which is incorporated by reference.

Disambiguating Terms with Structured Queries

In particular embodiments, in response to receiving a text querycomprising an ambiguous n-gram, the social-networking system 160 maygenerate a set of structured queries, where each structured query inthis set corresponds to an identified node or identified edgecorresponding to the ambiguous n-gram. Thus, each of these structuredqueries may comprise a reference to the corresponding identified node oridentified edge. For each identified node or identified edgecorresponding to the ambiguous n-gram, the social-networking system 160may generate at least one structured query referencing the identifiednode or identified edge. As discussed previously, these structuredqueries may be presented to the querying user, who can then select amongthe structured queries to indicate which social-graph element thequerying user intended to reference with the ambiguous term. In responseto the querying user's selection, the social-networking system 160 maythen lock the ambiguous term in the query to the social-graph elementselected by the querying user, and then generate a new set of structuredqueries based on the selected social-graph element. As an example andnot by way of limitation, referencing FIGS. 4C and 4D, in response toreceiving the unstructured text query “people who like facebook” inquery field 350, the social-networking system 160 may generate a set ofstructured queries, where each structured query references asocial-graph entity corresponding to one of the identified concept nodes204 that correspond to the ambiguous n-gram “facebook”. In this example,the set of structured queries includes references to “Facebook”,“Facebook Culinary Team”, and “Facebook Camera”, among others, each ofwhich may have been identified by the social-networking system 160 aspossibly corresponding to the ambiguous n-gram “facebook” from thereceived text query. The querying user may then select one of thestructured queries to select the particular concept referenced in thestructured query and thereby lock the structured query to the conceptnode 204 corresponding to the selected concept. For example, if thequerying user selected the first suggested structured query from thedrop-down menu 300 illustrated in FIG. 4C, “People who like Facebook”,then the social-networking system 160 may generate a new set ofstructured queries based on this selection, as illustrated in FIG. 4D,where the new set of structured queries in the drop-down menu 300 ofFIG. 4D all reference the concept node 204 for “Facebook” since that hasnow been locked to the previously ambiguous n-gram “facebook” from thereceived text query. Although this disclosure describes generatingparticular structured queries in response to particular ambiguous textqueries, this disclosure contemplates generating any suitable structuredqueries in response to any suitable ambiguous text queries.

In particular embodiments, a structured query may include a snippet ofcontextual information about one or more of the social-graph elementsreferenced in the structured query. Where the structured query isgenerated in response to a text query containing an ambiguous n-gram,the snippet may provide contextual information about the identified nodeor identified edge corresponding to the ambiguous n-gram that isreferenced in a particular structured query. The snippet included withthe structured query may be presented to the querying user (e.g., inlinewith the structured query in drop-down menu 300) to help aid the userdetermine whether the referenced social-graph element matches with theuser's intent. In particular embodiments, snippets may be includedautomatically with a structured query. When displaying a set ofstructured queries, a snippet of contextual information may beautomatically included with each structured query. In particularembodiments, a snippet may be included with a structured query when thequerying user interacts with the structured query. When the structuredqueries are initially presented to the querying user, a snippet may notbe necessarily included with each structured query. Instead, the snippetfor a particular structured query may be presented to the querying userafter the user interacts with the structured query, such as, forexample, by mousing over, focusing on, or otherwise interacting with thestructured query. As an example and not by way of limitation,referencing FIG. 4C, in response to the text query “people who likefacebook” in query field 350 (which contains the ambiguous term“facebook”), the social-networking system 160 has generated structuredqueries referencing the concept nodes 204 corresponding to the company“Facebook”, the group “Facebook Culinary Team”, among others, which arepresented to the user in drop-down menu 300. In the example illustratedin FIG. 4C, the querying user has focused on the structured query“People who like Facebook”, and in response a snippet reading“Product/Service—81,431,771 like this” has been generated next to thestructured query, where this snippet provides contextual informationabout the referenced concept node 204 for the company “Facebook”,indicating that it corresponds to a “Product/Service”. Furthermore, thissnippet provides contextual information about the referenced like-typeedge 206, indicating that “81,431,771 like this” (i.e., that number ofuser nodes 202 are connected to the concept node 204 for “Facebook” by alike-type edge 206). Similarly, were the user to focus on otherstructured queries displayed in drop-down menu 300 of FIG. 4C, differentsnippets may be displayed for each of those structured queries based onthe social-graph elements referenced in the particular structured query.Although this disclosure illustrates and describes generating particularsnippets for structured queries in a particular manner, this disclosurecontemplates generating any suitable snippets for structured queries inany suitable manner.

In particular embodiments, social-networking system 160 may transmit oneor more of the structured queries to the querying user. As an exampleand not by way of limitation, after the structured queries aregenerated, the social-networking system 160 may transmit one or more ofthe structured queries as a response (which may utilize AJAX or othersuitable techniques) to the user's client system 130 that may include,for example, the names (name strings) of the referenced social-graphelements, other query limitations (e.g., Boolean operators, etc.), aswell as, potentially, other metadata associated with the referencedsocial-graph elements. The web browser 132 on the querying user's clientsystem 130 may display the transmitted structured queries in a drop-downmenu 300, as illustrated in FIGS. 4A-4H. Where the structured queriesare generated in response to receiving a text query with an ambiguousn-gram, then the transmitted structured queries may be selectable by thequerying user to indicate that the identified node or identified edgesreference in the structured query match an intent of the user for theambiguous n-gram. As an example and not by way of limitation,referencing FIG. 4C, in response to the unstructured text query “peoplewho like facebook” in query field 350, the social-networking system 160may generate the set of structured queries illustrated in drop-down menu300. These structured queries include references to the concept nodes204 corresponding to “Facebook”, “Facebook Culinary Team”, and “FacebookCamera”, among others, each of which may have been identified by thesocial-networking system 160 as possibly corresponding to the ambiguousn-gram “facebook” from the received text query. The querying user maythen select one of these structured queries to select the particularconcept referenced in the structured query and thereby lock theambiguous n-gram “facebook” to the concept node 204 corresponding to theselected structured query. In particular embodiments, the transmittedqueries may be presented to the querying user in a ranked order, suchas, for example, based on a rank previously determined as describedabove. Structured queries with better rankings may be presented in amore prominent position. Furthermore, in particular embodiments, onlystructured queries above a threshold rank may be transmitted ordisplayed to the querying user. As an example and not by way oflimitation, as illustrated in FIGS. 4A-4B, the structured queries may bepresented to the querying user in a drop-down menu 300 where higherranked structured queries may be presented at the top of the menu, withlower ranked structured queries presented in descending order down themenu. In the examples illustrated in FIGS. 4A-4H, only the seven highestranked queries are transmitted and displayed to the user. In particularembodiments, one or more references in a structured query may behighlighted (e.g., outlined, underlined, circled, bolded, italicized,colored, lighted, offset, in caps) in order to indicate itscorrespondence to a particular social-graph element. As an example andnot by way of limitation, as illustrated in FIG. 4B, the references to“Stanford University” and “Stanford, Calif.” are highlighted (outlined)in the structured queries to indicate that it corresponds to aparticular concept node 204. Similarly, the references to “Friends”,“like”, “work at”, and “go to” in the structured queries presented indrop-down menu 300 could also be highlighted to indicate that theycorrespond to particular edges 206. Although this disclosure describestransmitting particular structured queries in a particular manner, thisdisclosure contemplates transmitting any suitable structured queries inany suitable manner.

In particular embodiments, social-networking system 160 may receive fromthe querying user a selection of one of the structured queries. Thenodes and edges referenced in the received structured query may bereferred to as the selected nodes and selected edges, respectively. Byselecting one of the structured queries generated in response to a textquery with an ambiguous n-gram, the querying user may be indicating thatthe node or edges referenced in the selected structured query match theintent of the user for the ambiguous n-gram. As an example and not byway of limitation, the web browser 132 on the querying user's clientsystem 130 may display the transmitted structured queries in a drop-downmenu 300, as illustrated in FIGS. 4A-4B, which the user may then clickon or otherwise select (e.g., by simply keying “enter” on his keyboard)to indicate the particular structured query the user wants thesocial-networking system 160 to execute. By selecting one of thestructured queries, the querying user may thereby lock the ambiguousn-gram to the social-graph element corresponding to the selectedstructured query. As an example and not by way of limitation,referencing FIG. 4C, the querying user may be inputted the unstructuredtext query “friends who like facebook” into query field 350, where theterm “facebook” in the text query has been identified as an ambiguousn-gram. If the querying user selects the second suggested structuredquery from the drop-down menu 300 illustrated in FIG. 4C, “People wholike Facebook Culinary Team”, which corresponds to the concept node 204for the group “Facebook Culinary Team”, then the social-networkingsystem 160 may lock the ambiguous n-gram “facebook” from the text queryto the concept node 204 for “Facebook Culinary Team” and generate a newset of structured queries based on this selection (i.e., a new set ofstructured queries that reference the concept node 204 for “FacebookCulinary Team”). Furthermore, upon selecting the particular structuredquery, the user's client system 130 may call or otherwise instruct tothe social-networking system 160 to execute the selected structuredquery. Although this disclosure describes receiving selections ofparticular structured queries in a particular manner, this disclosurecontemplates receiving selections of any suitable structured queries inany suitable manner.

In particular embodiments, in response to receiving a selection of astructured query from the querying user, the social-networking system160 may generate a new set of structured queries based on the selection.The selected structured query may comprise a reference to one of theidentified nodes or identified edges corresponding to the ambiguousn-gram. These identified nodes or identified edges may be referred to atthe selected nodes or selected edges, indicating that the particularsocial-graph element referenced in the structured query selected by thequerying user represents a social-graph element that the querying userspecifically intended to select. The structured queries of this new setmay comprise reference to the selected node or selected edge, and mayfurther comprise reference to zero or more additional nodes and zero ormore additional edges. In this way, the suggested structured queriesgenerated by the social-networking system 160 may expanded off of theuser's selection, where the querying user effectively selects the baseof the query to use for generating more complex queries. As an exampleand not by way of limitation, the drop-down menu 300 illustrated in FIG.4D shows a set of structured queries generated in response to thequerying user's selection of the suggested structured query “People wholike Facebook” from FIG. 4C. The suggested structured query “People wholike Facebook” corresponded to the concept node 204 for the company“Facebook”, which had been identified as a concept node 204 thatcorresponded to the ambiguous n-gram “facebook” from the unstructuredtext query in query field 350 of FIG. 4C. After selecting thisstructured query, the ambiguous n-gram “facebook” was locked to theconcept node 204 for the company “Facebook” and the social-networkingsystem 160 then generated a new set of structured queries thatreferenced this concept node 204, along with additional social-graphelements. The selected structured query may also be used to replace theunstructured text query previously received in the query field 350. Forexample, once the querying user selected the structured query “Peoplewho like Facebook” from the drop-down menu 300 in FIG. 4C, that selectedstructured query may replace the original text query, and thesocial-networking system 160 may auto-populate the query field 350 withthe selected structured query, as illustrated in FIG. 4D, where thequery field 350 is now populated with the previously selected structuredquery. In particular embodiments, the querying user may then continue toinput text into query field 350 to further modify the query, forexample, by adding a text string before, into, or after the structuredquery that has been populated into the query field 350. In this way, thestructured query may be further refined by the querying user.Furthermore, the processes described above may be repeated in responseto the input of additional ambiguous n-grams. Thus, thesocial-networking system 160 may parse the unstructured text queryportion of a query that has been inputted into query field 350. Althoughthis disclosure describes generating structured queries in response to auser's selection in a particular manner, this disclosure contemplatesgenerating structured queries in response to a user's selection in anysuitable manner.

FIG. 5 illustrates an example method 500 for disambiguating terms intext queries to generate structured search queries. The method may beginat step 510, where the social-networking system 160 may access a socialgraph 200 comprising a plurality of nodes and a plurality of edges 206connecting the nodes. The nodes may comprise a first user node 202 and aplurality of second nodes (one or more user nodes 202, concepts nodes204, or any combination thereof). At step 520, the social-networkingsystem 160 may receive from the first user an unstructured text querythat comprises an ambiguous n-gram. At step 530, the social-networkingsystem 160 may a plurality of second nodes or a plurality of edgescorresponding to the ambiguous n-gram. For example, thesocial-networking system 160 may identify two different nodes that matchthe ambiguous n-gram from the text query. At step 540, thesocial-networking system 160 may generate a first set of structuredqueries. Each of these structured queries may correspond to anidentified second node or identified edge, and each structure query mayinclude a reference to that identified second node or identified edge.For example, the social-networking system 160 may generate onestructured query with a reference to a particular node and anotherstructured query with a reference to another node, where both nodespossibly match the ambiguous n-gram. At step 550, the social-networkingsystem 160 may receive from the first user a selection of a firststructured query from the first set of structured queries. The firststructured query may correspond to a selected second node or selectededge from the identified second nodes or identified edges, respectively.In this way, the first user may disambiguate the ambiguous n-gram byindicating an intent that the n-gram matches the selected social-graphelement references from the selected structured query. At step 560, thesocial-networking system 160 may generate a second set of structuredqueries. Each structured query of the second set of structured queriesmay comprise a reference to the selected second node or selected edge.Thus, in response to the first user's selection, the social-networkingsystem 160 may generate a new set of structured queries that takes intoaccount the disambiguated n-gram. Particular embodiments may repeat oneor more steps of the method of FIG. 5, where appropriate. Although thisdisclosure describes and illustrates particular steps of the method ofFIG. 5 as occurring in a particular order, this disclosure contemplatesany suitable steps of the method of FIG. 5 occurring in any suitableorder. Moreover, although this disclosure describes and illustratesparticular components, devices, or systems carrying out particular stepsof the method of FIG. 5, this disclosure contemplates any suitablecombination of any suitable components, devices, or systems carrying outany suitable steps of the method of FIG. 5.

More information on structured search queries may be found in U.S.patent application Ser. No. 13/556,072, filed 23 Jul. 2012, and U.S.patent application Ser. No. 13/674,695, filed 12 Nov. 2012, each ofwhich is incorporated by reference.

Generating Default Queries for a Page

FIGS. 6A-6F illustrate example webpages of an online social network. Inparticular embodiments, the social-networking system 160 may generate aset of default structured queries for a page of the online socialnetwork. The social-networking system 160 may identify a page that auser is currently viewing or otherwise accessing and then identifyingany social-graph elements corresponding to that page. The social-graphelements corresponding to a page may be, for example, the nodecorresponding to a user- or concept-profile page, or the nodes/edgesreferenced in a structured query used to generate a particularsearch-results page. The social-networking system 160 may then generatea set of default structured queries for the page based on the identifiedsocial-graph elements for that page. As an example and not by way oflimitation, referencing FIG. 6B, when accessing a user-profile page forthe user “Mark”, which corresponds to the user node 202 for “Mark”, someof the default structured queries for that page may include “Friends ofMark” or “Photos of Mark”, as illustrated in drop-down menu 300, whereeach of these structured queries includes a reference to the user node202 of the user “Mark”. The generated default structured queries maythen be transmitted to the user and displayed, for example, in adrop-down menu 300. In particular embodiments, the query field 350 mayalso serve as the title bar for the page. In other words, the title barand query field 350 may effectively be a unified field on a particularpage. The title bar for a page of the online social network may includea reference to the social-graph elements that correspond to that page.As an example and not by way of limitation, referencing is user-profilepages illustrated in FIGS. 6C-6D, the title bar across the top of thepage includes the name of the concept corresponding to that page,“Barack Obama”. As another example and not by way of limitation,referencing the search-results pages illustrated in FIGS. 6E-6F, thetitle bar across the top of the page includes the structured query usedto generate the page, “Current Facebook employees”. This title bar mayalso server as a query field 350 for the page. As such, a user accessingthat page may then interact with the title of the page (e.g., by mousingover the title, clicking on it, or otherwise interacting with it), toinput a query. In response to a user interacting with the title/queryfield, the social-networking system 160 may then generate a set ofdefault structured queries for the page and automatically transmit anddisplay these queries in a drop-down menu 300 on the page, asillustrated in FIG. 6B, where the drop-down menu 300 is displayed inassociation with the query field 350. Although this disclosure describesgenerating default queries for a page in a particular manner, thisdisclosure contemplates generating default queries for a page in anysuitable manner.

In particular embodiments, the social-networking system 160 may identifya node of the social-graph 200 corresponding to a page currentlyaccessed by a user. A user may access any suitable page, such as, forexample, a user-profile page, a concept-profile page, a search-resultspage, a homepage, a newsfeed page, an email or messages page, or anothersuitable page of the online social network. Particular pages of theonline social network may correspond to particular social-graphelements. In particular embodiments, the user may currently be accessinga profile page of the online social network corresponding to aparticular user node 202 or concept node 204. Each user of the onlinesocial network may have a user-profile page that corresponds to a usernode 202 of the user. As an example and not by way of limitation,referencing FIGS. 6A-6B, which illustrate a user-profile page for theuser “Mark”, this page may correspond to a user node 202 of the user“Mark”. Similarly, each concept represented in the online social networkmay have a concept-profile page that corresponds to a concept node 204representing that concept. As an example and not by way of limitation,referencing FIGS. 6C-6D, which illustrate a concept-profile page for thepolitician “Barack Obama”, this page may correspond to a concept node204 representing the politician “Barack Obama” (note, of course, thatBarack Obama may also have a personal user-profile page). In particularembodiments, the user may currently be accessing a search-results pagecorresponding to a structured query. The structured query may comprisereferences to one or more nodes and one or more edges, and thesearch-results page may have been generated in response to thisstructured query. In this case, one or more of the nodes referenced inthe structured query may be identified by the social-networking system160 as being the nodes corresponding to the page. As an example and notby way of limitation, referencing FIGS. 6E-6F, which illustrate asearch-results page generated by the structured query “Current Facebookemployees” (which includes a reference to the concept node 204 for thecompany “Facebook”), the social-networking system 160 may identify theconcept node 204 corresponding to the company “Facebook” as being thenode corresponding to this search-results page. Although this disclosuredescribes identifying particular nodes corresponding to particular pagesin a particular manner, this disclosure contemplates identifying anysuitable nodes corresponding to any suitable pages in any suitablemanner.

In particular embodiments, the social-networking system 160 may generateone or more structured queries that each comprise a reference to theidentified node(s) of the page currently accessed by a user. Thesegenerated structured queries may be considered the default structuredqueries for the page. Each of these structured queries may also comprisereferences to one or more edges that are connected to the identifiednode. These default structured queries are effectively based on andreference the page currently being accessed by the user. Where the titlebar and the query field 350 field are unified fields, as describedpreviously, the social-networking system 160 may essentially use thetitle of the page (which itself may be considered a reference to one ormore social-graph elements) as a template query upon which querymodifications are added to generate the default structured queries. Asan example and not by way of limitation, referencing FIG. 6D, the titleof the page is “Barack Obama”, where this title is unified with thequery field 350, such that a user may interact with the title toimmediately bring up a drop-down menu 300 with a set of default queriesfor the page that reference the page the user is interacting with (i.e.,the suggested default queries contain references to the concept-node 204associated with the concept “Barack Obama”). In particular embodiments,if the user is accessing a search-results page, then the defaultstructured queries generated by the social-networking system 160 maycomprises references to the social-graph elements referenced in thestructured query used to generate that search-results page. In otherwords, if a structured query comprising references to one or more nodesand one or more edges is used to generate a particular search-resultspage, then the default structured queries generated for that page willalso include at least references to the one or more nodes and one ormore edges of the original structured query. Thus, the structured queryused to generate a particular search-results page may be used as thebase upon which expansions of that initial query may be suggested asdefault queries. As an example and not by way of limitation, referencingFIG. 6F, the title of the page is “Current Facebook employees”, wherethis title is also a structured query that was used to generate thesearch-results page and has now been populated into query field 350.When the user interacts with the query field, the social-networkingsystem 160 may generate a set of default structured queries based on theoriginal structure query, where each of the default structured queriesis effectively a modification of the original query “Current Facebookemployees”. For example, in the example illustrated in FIG. 6F, thesocial-networking system 160 has generated the suggested defaultstructured queries “Current Facebook employees who live in Austin, Tex.”(which references the additional social-graph elements of a live-in-typeedge 206 and a concept node 204 for “Austin, Tex.”) and “CurrentFacebook employees who like Old Pro” (which references the additionalsocial-graph elements of a like-type edge 206 and a concept node 204 for“Old Pro), where each of these references the social-graph elements fromthe original structured query as well as additional social-graphelements that are modifications of the original query. Although thisdisclosure describes generating particular default structured queries ina particular manner, this disclosure contemplates any suitable defaultstructured queries in any suitable manner. Moreover, although thisdisclosure describes generating default structured queries forparticular types of pages, this disclosure contemplates generatingdefault structured queries for any suitable types of pages.

In particular embodiments, the social-networking system 160 may transmitone or more of the default structured queries to the querying user fordisplay on the page currently accessed by the user. These structuredqueries may be transmitted and displayed as previously described. As anexample and not by way of limitation, the web browser 132 on thequerying user's client system 130 may display the transmitted structuredqueries in a drop-down menu 300 in association with a query field 350 ofa webpage, as illustrated in FIGS. 6B, 6D, and 6F. The defaultstructured queries generated for a particular page may not be displayeduntil the user interacts with the query field 350, such as, for example,by mousing over or clicking on the query field 350, which may cause thestructured queries to be transmitted and displayed in drop-down menu300. The structured queries displayed in drop-down menu 300 may enablethe user accessing the page to selected one of the structured queries,indicating that the selected structured query should be executed by thesocial-networking system 160. Although this disclosure describestransmitting particular default structured queries in a particularmanner, this disclosure contemplates transmitting any suitable defaultstructured queries in any suitable manner.

In particular embodiments, the social-networking system 160 may generateone or more default structured queries in response to a user accessing apage that does not correspond to a particular social-graph element. Auser may access a page of the online social network that does notnecessarily correspond to any particular social-graph element (such as,for example, a newsfeed page, which may not necessarily correspond toany particular nodes or edges of the social graph 200). In this case,the page may be considered to be in a “null state” with respect toidentifying social-graph elements that correspond to the page.Similarly, for a page that does correspond to one or more social-graphelements, the user accessing that page may place the query field 350 ofthe page into a null state by, for example, clearing or deleting anytitle or query that that had previously occupied the field. For anull-state page (or a query field 350 in a null state), thesocial-networking system 160 may generate a set of default structuredqueries for the page based on a variety of factors, such as, forexample, the type of page the user is accessing, the query history ofthe user, the general or current popularity of particular queries, theusefulness of particular queries, other suitable factors, or anycombination thereof. These default structured queries may bepre-generated and accessed from a cache or generated dynamically inresponse to input from the user. In particular embodiments, when theuser is accessing a page that does not correspond to a particularsocial-graph element, the social-networking system 160 may access a setof default structured queries corresponding to the page. Each of thesedefault structured queries may comprise references to one or more edges206 (or edge-types) or one or more nodes (or node-types). As an exampleand not by way of limitation, FIG. 3 illustrates a newsfeed page beingaccessed by a user of the online social network. Some of the defaultstructured queries for this page may include “Friends of . . . ” or“People who like . . . ”, as illustrated in drop-down menu 300, wherethese structured queries included references to friend-type edges 206and like-type edges 206, respectively. In the example illustrated inFIG. 3, the default structured queries contain ellipses to indicate thatthe user may input text into the query field 350 to complete the query.As another example and not by way of limitation, for the same newsfeedpage illustrated in FIG. 3, the social-networking system 160 maygenerate default structured queries that include “My friends”, “Photosof my friends”, “Photos I like”, or “Apps my friends use”, where thesestructured queries include reference to both edges and nodes (e.g., forthe structured query “My friends”, the term “My” is a reference to theuser node 202 of the querying user and the term “friends” is a referenceto friend-type edges 206 connected to that node). Although thisdisclosure describes generating default structured queries for a pagethat does not correspond to particular social-graph elements in aparticular manner, this disclosure contemplates generating defaultstructured queries for a page that does not correspond to particularsocial-graph elements in any suitable manner.

FIG. 7 illustrates an example method 700 for generating defaultstructured search queries for a page. The method may begin at step 710,where the social-networking system 160 may access a social graph 200comprising a plurality of nodes and a plurality of edges 206 connectingthe nodes. The nodes may comprise a first user node 202 and a pluralityof second nodes (one or more user nodes 202, concepts nodes 204, or anycombination thereof). At step 720, the social-networking system 160 mayidentify a node of the plurality of nodes corresponding to a pagecurrently accessed by the first user. The page may be, for example, auser-profile page, a concept-profile page, a search-results page, oranother suitable page of the online social network. At step 730, thesocial-networking system 160 may generate one or more structuredqueries. Each of these structured queries may reference the identifiednode corresponding to the page currently accessed by the first user. Thestructured queries may also reference one or more edges of the pluralityof edges that are connected to the identified node. At step 740, thesocial-networking system 160 may transmit one or more of the structuredqueries to the first user for display on the page. These may beconsidered the default structured queries for the page, which have beendetermined based on the social-graph elements associated with the page.Particular embodiments may repeat one or more steps of the method ofFIG. 7, where appropriate. Although this disclosure describes andillustrates particular steps of the method of FIG. 7 as occurring in aparticular order, this disclosure contemplates any suitable steps of themethod of FIG. 7 occurring in any suitable order. Moreover, althoughthis disclosure describes and illustrates particular components,devices, or systems carrying out particular steps of the method of FIG.7, this disclosure contemplates any suitable combination of any suitablecomponents, devices, or systems carrying out any suitable steps of themethod of FIG. 7.

Generating Search Results

In particular embodiments, in response to a structured query receivedfrom a querying user, the social-networking system 160 may generate oneor more search results, where each search result matches (orsubstantially matches) the terms of the structured query. Thesocial-networking system 160 may receive a structured query from aquerying user (also referred to as the “first user”, corresponding to afirst user node 202). In response to the structured query, thesocial-networking system 160 may generate one or more search resultscorresponding to the structured query. Each search result may includelink to a profile page and a description or summary of the profile page(or the node corresponding to that page). The search results may bepresented and transmitted to the querying user as a search-results page.FIG. 6E illustrates an example search-results page generated in responseto a particular structured query. The structured query used to generatea particular search-results page is shown in query field 350, and thevarious search results generated in response to the structured query areillustrated in a field for presented search results. In particularembodiments, the query field 350 may also serve as the title bar for thepage. In other words, the title bar and query field 350 may effectivelybe a unified field on the search-results page. As an example, FIG. 6Eillustrates a search-results page with the structured query “CurrentFacebook employees” in query field 350. This structured query alsoeffectively serves as the title for the generated page, where the pageshows a plurality search results of users of the online social networkwho are employees at the company “Facebook”. The search-results page mayalso include a field for modifying search results and a field forproviding suggested searches. When generating the search results, thesocial-networking system 160 may generate one or more snippets for eachsearch result, where the snippets are contextual information about thetarget of the search result (i.e., contextual information about thesocial-graph entity, profile page, or other content corresponding to theparticular search result). Although this disclosure describes andillustrates particular search-results pages, this disclosurecontemplates any suitable search-results pages.

More information on generating search results may be found in U.S.patent application Ser. No. 13/731,939, filed 31 Dec. 2012, which isincorporated by reference.

Systems and Methods

FIG. 8 illustrates an example computer system 800. In particularembodiments, one or more computer systems 800 perform one or more stepsof one or more methods described or illustrated herein. In particularembodiments, one or more computer systems 800 provide functionalitydescribed or illustrated herein. In particular embodiments, softwarerunning on one or more computer systems 800 performs one or more stepsof one or more methods described or illustrated herein or providesfunctionality described or illustrated herein. Particular embodimentsinclude one or more portions of one or more computer systems 800.Herein, reference to a computer system may encompass a computing device,and vice versa, where appropriate. Moreover, reference to a computersystem may encompass one or more computer systems, where appropriate.

This disclosure contemplates any suitable number of computer systems800. This disclosure contemplates computer system 800 taking anysuitable physical form. As example and not by way of limitation,computer system 800 may be an embedded computer system, a system-on-chip(SOC), a single-board computer system (SBC) (such as, for example, acomputer-on-module (COM) or system-on-module (SOM)), a desktop computersystem, a laptop or notebook computer system, an interactive kiosk, amainframe, a mesh of computer systems, a mobile telephone, a personaldigital assistant (PDA), a server, a tablet computer system, or acombination of two or more of these. Where appropriate, computer system800 may include one or more computer systems 800; be unitary ordistributed; span multiple locations; span multiple machines; spanmultiple data centers; or reside in a cloud, which may include one ormore cloud components in one or more networks. Where appropriate, one ormore computer systems 800 may perform without substantial spatial ortemporal limitation one or more steps of one or more methods describedor illustrated herein. As an example and not by way of limitation, oneor more computer systems 800 may perform in real time or in batch modeone or more steps of one or more methods described or illustratedherein. One or more computer systems 800 may perform at different timesor at different locations one or more steps of one or more methodsdescribed or illustrated herein, where appropriate.

In particular embodiments, computer system 800 includes a processor 802,memory 804, storage 806, an input/output (I/O) interface 808, acommunication interface 810, and a bus 812. Although this disclosuredescribes and illustrates a particular computer system having aparticular number of particular components in a particular arrangement,this disclosure contemplates any suitable computer system having anysuitable number of any suitable components in any suitable arrangement.

In particular embodiments, processor 802 includes hardware for executinginstructions, such as those making up a computer program. As an exampleand not by way of limitation, to execute instructions, processor 802 mayretrieve (or fetch) the instructions from an internal register, aninternal cache, memory 804, or storage 806; decode and execute them; andthen write one or more results to an internal register, an internalcache, memory 804, or storage 806. In particular embodiments, processor802 may include one or more internal caches for data, instructions, oraddresses. This disclosure contemplates processor 802 including anysuitable number of any suitable internal caches, where appropriate. Asan example and not by way of limitation, processor 802 may include oneor more instruction caches, one or more data caches, and one or moretranslation lookaside buffers (TLBs). Instructions in the instructioncaches may be copies of instructions in memory 804 or storage 806, andthe instruction caches may speed up retrieval of those instructions byprocessor 802. Data in the data caches may be copies of data in memory804 or storage 806 for instructions executing at processor 802 tooperate on; the results of previous instructions executed at processor802 for access by subsequent instructions executing at processor 802 orfor writing to memory 804 or storage 806; or other suitable data. Thedata caches may speed up read or write operations by processor 802. TheTLBs may speed up virtual-address translation for processor 802. Inparticular embodiments, processor 802 may include one or more internalregisters for data, instructions, or addresses. This disclosurecontemplates processor 802 including any suitable number of any suitableinternal registers, where appropriate. Where appropriate, processor 802may include one or more arithmetic logic units (ALUs); be a multi-coreprocessor; or include one or more processors 802. Although thisdisclosure describes and illustrates a particular processor, thisdisclosure contemplates any suitable processor.

In particular embodiments, memory 804 includes main memory for storinginstructions for processor 802 to execute or data for processor 802 tooperate on. As an example and not by way of limitation, computer system800 may load instructions from storage 806 or another source (such as,for example, another computer system 800) to memory 804. Processor 802may then load the instructions from memory 804 to an internal registeror internal cache. To execute the instructions, processor 802 mayretrieve the instructions from the internal register or internal cacheand decode them. During or after execution of the instructions,processor 802 may write one or more results (which may be intermediateor final results) to the internal register or internal cache. Processor802 may then write one or more of those results to memory 804. Inparticular embodiments, processor 802 executes only instructions in oneor more internal registers or internal caches or in memory 804 (asopposed to storage 806 or elsewhere) and operates only on data in one ormore internal registers or internal caches or in memory 804 (as opposedto storage 806 or elsewhere). One or more memory buses (which may eachinclude an address bus and a data bus) may couple processor 802 tomemory 804. Bus 812 may include one or more memory buses, as describedbelow. In particular embodiments, one or more memory management units(MMUs) reside between processor 802 and memory 804 and facilitateaccesses to memory 804 requested by processor 802. In particularembodiments, memory 804 includes random access memory (RAM). This RAMmay be volatile memory, where appropriate Where appropriate, this RAMmay be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, whereappropriate, this RAM may be single-ported or multi-ported RAM. Thisdisclosure contemplates any suitable RAM. Memory 804 may include one ormore memories 804, where appropriate. Although this disclosure describesand illustrates particular memory, this disclosure contemplates anysuitable memory.

In particular embodiments, storage 806 includes mass storage for data orinstructions. As an example and not by way of limitation, storage 806may include a hard disk drive (HDD), a floppy disk drive, flash memory,an optical disc, a magneto-optical disc, magnetic tape, or a UniversalSerial Bus (USB) drive or a combination of two or more of these. Storage806 may include removable or non-removable (or fixed) media, whereappropriate. Storage 806 may be internal or external to computer system800, where appropriate. In particular embodiments, storage 806 isnon-volatile, solid-state memory. In particular embodiments, storage 806includes read-only memory (ROM). Where appropriate, this ROM may bemask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM),electrically erasable PROM (EEPROM), electrically alterable ROM (EAROM),or flash memory or a combination of two or more of these. Thisdisclosure contemplates mass storage 806 taking any suitable physicalform. Storage 806 may include one or more storage control unitsfacilitating communication between processor 802 and storage 806, whereappropriate. Where appropriate, storage 806 may include one or morestorages 806. Although this disclosure describes and illustratesparticular storage, this disclosure contemplates any suitable storage.

In particular embodiments, I/O interface 808 includes hardware,software, or both, providing one or more interfaces for communicationbetween computer system 800 and one or more I/O devices. Computer system800 may include one or more of these I/O devices, where appropriate. Oneor more of these I/O devices may enable communication between a personand computer system 800. As an example and not by way of limitation, anI/O device may include a keyboard, keypad, microphone, monitor, mouse,printer, scanner, speaker, still camera, stylus, tablet, touch screen,trackball, video camera, another suitable I/O device or a combination oftwo or more of these. An I/O device may include one or more sensors.This disclosure contemplates any suitable I/O devices and any suitableI/O interfaces 808 for them. Where appropriate, I/O interface 808 mayinclude one or more device or software drivers enabling processor 802 todrive one or more of these I/O devices. I/O interface 808 may includeone or more I/O interfaces 808, where appropriate. Although thisdisclosure describes and illustrates a particular I/O interface, thisdisclosure contemplates any suitable I/O interface.

In particular embodiments, communication interface 810 includeshardware, software, or both providing one or more interfaces forcommunication (such as, for example, packet-based communication) betweencomputer system 800 and one or more other computer systems 800 or one ormore networks. As an example and not by way of limitation, communicationinterface 810 may include a network interface controller (NIC) ornetwork adapter for communicating with an Ethernet or other wire-basednetwork or a wireless NIC (WNIC) or wireless adapter for communicatingwith a wireless network, such as a WI-FI network. This disclosurecontemplates any suitable network and any suitable communicationinterface 810 for it. As an example and not by way of limitation,computer system 800 may communicate with an ad hoc network, a personalarea network (PAN), a local area network (LAN), a wide area network(WAN), a metropolitan area network (MAN), or one or more portions of theInternet or a combination of two or more of these. One or more portionsof one or more of these networks may be wired or wireless. As anexample, computer system 800 may communicate with a wireless PAN (WPAN)(such as, for example, a BLUETOOTH WPAN), a WI-FI network, a WI-MAXnetwork, a cellular telephone network (such as, for example, a GlobalSystem for Mobile Communications (GSM) network), or other suitablewireless network or a combination of two or more of these. Computersystem 800 may include any suitable communication interface 810 for anyof these networks, where appropriate. Communication interface 810 mayinclude one or more communication interfaces 810, where appropriate.Although this disclosure describes and illustrates a particularcommunication interface, this disclosure contemplates any suitablecommunication interface.

In particular embodiments, bus 812 includes hardware, software, or bothcoupling components of computer system 800 to each other. As an exampleand not by way of limitation, bus 812 may include an AcceleratedGraphics Port (AGP) or other graphics bus, an Enhanced Industry StandardArchitecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT)interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBANDinterconnect, a low-pin-count (LPC) bus, a memory bus, a Micro ChannelArchitecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, aPCI-Express (PCIe) bus, a serial advanced technology attachment (SATA)bus, a Video Electronics Standards Association local (VLB) bus, oranother suitable bus or a combination of two or more of these. Bus 812may include one or more buses 812, where appropriate. Although thisdisclosure describes and illustrates a particular bus, this disclosurecontemplates any suitable bus or interconnect.

Herein, a computer-readable non-transitory storage medium or media mayinclude one or more semiconductor-based or other integrated circuits(ICs) (such, as for example, field-programmable gate arrays (FPGAs) orapplication-specific ICs (ASICs)), hard disk drives (HDDs), hybrid harddrives (HHDs), optical discs, optical disc drives (ODDs),magneto-optical discs, magneto-optical drives, floppy diskettes, floppydisk drives (FDDs), magnetic tapes, solid-state drives (SSDs),RAM-drives, SECURE DIGITAL cards or drives, any other suitablecomputer-readable non-transitory storage media, or any suitablecombination of two or more of these, where appropriate. Acomputer-readable non-transitory storage medium may be volatile,non-volatile, or a combination of volatile and non-volatile, whereappropriate.

Miscellaneous

Herein, “or” is inclusive and not exclusive, unless expressly indicatedotherwise or indicated otherwise by context. Therefore, herein, “A or B”means “A, B, or both,” unless expressly indicated otherwise or indicatedotherwise by context. Moreover, “and” is both joint and several, unlessexpressly indicated otherwise or indicated otherwise by context.Therefore, herein, “A and B” means “A and B, jointly or severally,”unless expressly indicated otherwise or indicated otherwise by context.

The scope of this disclosure encompasses all changes, substitutions,variations, alterations, and modifications to the example embodimentsdescribed or illustrated herein that a person having ordinary skill inthe art would comprehend. The scope of this disclosure is not limited tothe example embodiments described or illustrated herein. Moreover,although this disclosure describes and illustrates respectiveembodiments herein as including particular components, elements,functions, operations, or steps, any of these embodiments may includeany combination or permutation of any of the components, elements,functions, operations, or steps described or illustrated anywhere hereinthat a person having ordinary skill in the art would comprehend.Furthermore, reference in the appended claims to an apparatus or systemor a component of an apparatus or system being adapted to, arranged to,capable of, configured to, enabled to, operable to, or operative toperform a particular function encompasses that apparatus, system,component, whether or not it or that particular function is activated,turned on, or unlocked, as long as that apparatus, system, or componentis so adapted, arranged, capable, configured, enabled, operable, oroperative.

What is claimed is:
 1. A method comprising, by a computing device:receiving, from a client system of a first user, a character stringhaving n characters entered by the first user into a query field,wherein a term comprising the n^(th) character of the character stringis an ambiguous term; identifying one or more objects corresponding tothe ambiguous term based on a calculated probability that the ambiguousterm corresponds to the identified objects; sending, to the clientsystem responsive to receiving the n^(th) character of the characterstring, instructions for presenting a set of suggested queries to thefirst user, each suggested query from the set of suggested queriescorresponding to one of the identified objects and comprising areference to the corresponding identified object; receiving, from theclient system, a selection of a suggested query corresponding to a firstobject of the identified objects; and sending, to the client systemresponsive to receiving the selection of the suggested query,instructions for modifying the ambiguous term in the query field toinclude a reference to the first object.
 2. The method of claim 1,further comprising: generating one or more suggested queriescorresponding to one or more of the identified objects, respectively,wherein the set of suggested queries presented to the first usercomprises one or more of the generated suggested queries.
 3. The methodof claim 1, wherein receiving the character string having n charactersentered by the first user into the query field comprises receiving eachcharacter of the character string as the first user at the client systementers the character string into the query field.
 4. The method of claim3, wherein the query field is part of a user interface of a nativeapplication associated with an online social network on the clientsystem of the first user.
 5. The method of claim 3, wherein the queryfield is part of a webpage of an online social network accessed by abrowser client on the client system of the first user.
 6. The method ofclaim 3, wherein the query field is part of a user interface of amessaging application on the client system of the first user.
 7. Themethod of claim 1, wherein for each suggested query from the set ofsuggested queries, the reference to the corresponding identified objectis highlighted to indicate the reference corresponds to the ambiguousterm.
 8. The method of claim 1, wherein for each suggested query fromthe set of suggested queries, the suggested query further comprises asnippet comprising contextual information about the identified objectcorresponding to the suggested query.
 9. The method of claim 1, whereineach suggested query from the set of suggested queries is selectable bythe first user to indicate that the identified object referenced in thesuggested query matches an intent of the user for the ambiguous term.10. The method of claim 1, further comprising: presenting, at the clientsystem, one or more suggested queries from the set of suggested queries,the presentation of the one or more suggested queries enabling the firstuser to select one of the suggested queries.
 11. The method of claim 1,further comprising: sending, to the client system, instructions forpresenting an updated set of suggested queries to the first user, eachsuggested query from the updated set of suggested queries correspondingto a particular object and comprising a reference to the correspondingparticular object; and receiving, from the client system, a selection ofa suggested query from the updated set of suggested queriescorresponding to one of the particular objects.
 12. The method of claim1, further comprising: generating one or more search resultscorresponding to the character string modified by the ambiguous term;and sending, to the client system, instructions for presenting asearch-results interface to the first user, the search-results interfacecomprising one or more of the search results.
 13. The method of claim 1,wherein identifying one or more objects corresponding to the ambiguousterm comprises: determining, for each of a plurality of objects matchingthe ambiguous term at least in part, a score for the object representinga probability that the ambiguous term corresponds to the object; andidentifying each object having a score greater than a threshold score,wherein at least two objects have a score greater than the thresholdscore.
 14. The method of claim 13, wherein determining the score isbased on the degree of separation between the first user and the objectwithin a social graph of an online social network.
 15. The method ofclaim 13, wherein determining the score is based on a search historyassociated with the first user.
 16. The method of claim 1, furthercomprising: accessing a social graph associated with an online socialnetwork, the social graph comprising a plurality of nodes and aplurality of edges connecting the nodes, each of the edges between twoof the nodes representing a single degree of separation between them,the nodes comprising: a first node corresponding to the first user; anda plurality of second nodes that each correspond to an object of theplurality of objects associated with the online social network.
 17. Themethod of claim 16, wherein each suggested query is structured querycomprising references to one or more nodes of the plurality of nodes orone or more edges of the plurality of edges.
 18. The method of claim 16,wherein modifying the ambiguous term comprises replacing the ambiguousterm with a reference to a node of the plurality of nodes correspondingto the first identified object.
 19. One or more computer-readablenon-transitory storage media embodying software that is operable whenexecuted to: receive, from a client system of a first user, a characterstring having n characters entered by the first user into a query field,wherein a term comprising the n^(th) character of the character stringis an ambiguous term; identify one or more objects corresponding to theambiguous term based on a calculated probability that the ambiguous termcorresponds to the identified objects; send, to the client systemresponsive to receiving the n^(th) character of the character string,instructions for presenting a set of suggested queries to the firstuser, each suggested query from the set of suggested queriescorresponding to one of the identified objects and comprising areference to the corresponding identified object; receive, from theclient system, a selection of a suggested query corresponding to a firstobject of the identified objects; and send, to the client systemresponsive to receiving the selection of the suggested query,instructions for modifying the ambiguous term in the query field toinclude a reference to the first object.
 20. A system comprising: one ormore processors; and a memory coupled to the processors comprisinginstructions executable by the processors, the processors operable whenexecuting the instructions to: receive, from a client system of a firstuser, a character string having n characters entered by the first userinto a query field, wherein a term comprising the n^(th) character ofthe character string is an ambiguous term; identify one or more objectscorresponding to the ambiguous term based on a calculated probabilitythat the ambiguous term corresponds to the identified objects; send, tothe client system responsive to receiving the n^(th) character of thecharacter string, instructions for presenting a set of suggested queriesto the first user, each suggested query from the set of suggestedqueries corresponding to one of the identified objects and comprising areference to the corresponding identified object; receive, from theclient system, a selection of a suggested query corresponding to a firstobject of the identified objects; and send, to the client systemresponsive to receiving the selection of the suggested query,instructions for modifying the ambiguous term in the query field toinclude a reference to the first object.